diff --git "a/scores/gemma-4-26B-A4B-it-Q3_K.md" "b/scores/gemma-4-26B-A4B-it-Q3_K.md" new file mode 100644--- /dev/null +++ "b/scores/gemma-4-26B-A4B-it-Q3_K.md" @@ -0,0 +1,1742 @@ +# gemma-4-26B-A4B-it-Q3_K.gguf - GGUF Internal File Dump + +- Endian: LITTLE endian + +## Key Value Metadata Store + +There are 57 key-value pairs in this file + +| POS | TYPE | Count | Key | Value | +| ---: | :-------- | -----: | :-------------------------------------- | :--------------------------------------------------------------------------------------------------------------- | +| 1 | UINT32 | 1 | GGUF.version | 3 | +| 2 | UINT64 | 1 | GGUF.tensor_count | 658 | +| 3 | UINT64 | 1 | GGUF.kv_count | 54 | +| 4 | STRING | 1 | general.architecture | `gemma4` | +| 5 | STRING | 1 | general.type | `model` | +| 6 | INT32 | 1 | general.sampling.top_k | 64 | +| 7 | FLOAT32 | 1 | general.sampling.top_p | 0.95 | +| 8 | FLOAT32 | 1 | general.sampling.temp | 1.0 | +| 9 | STRING | 1 | general.name | `Gemma 4 26B A4B It` | +| 10 | STRING | 1 | general.finetune | `it` | +| 11 | STRING | 1 | general.basename | `gemma-4` | +| 12 | STRING | 1 | general.size_label | `26B-A4B` | +| 13 | STRING | 1 | general.license | `apache-2.0` | +| 14 | STRING | 1 | general.license.link | `https://ai.google.dev/gemma/docs/gemma_4_license` | +| 15 | [STRING] | 1 | general.tags | [ `image-text-to-text` ] | +| 16 | UINT32 | 1 | gemma4.block_count | 30 | +| 17 | UINT32 | 1 | gemma4.context_length | 262144 | +| 18 | UINT32 | 1 | gemma4.embedding_length | 2816 | +| 19 | UINT32 | 1 | gemma4.feed_forward_length | 2112 | +| 20 | UINT32 | 1 | gemma4.attention.head_count | 16 | +| 21 | [INT32] | 30 | gemma4.attention.head_count_kv | [ 8, 8, 8, 8, 8, 2, 8, ... ] | +| 22 | FLOAT32 | 1 | gemma4.rope.freq_base | 1e+06 | +| 23 | FLOAT32 | 1 | gemma4.rope.freq_base_swa | 10000.0 | +| 24 | FLOAT32 | 1 | gemma4.attention.layer_norm_rms_epsilon | 1e-06 | +| 25 | UINT32 | 1 | gemma4.expert_count | 128 | +| 26 | UINT32 | 1 | gemma4.expert_used_count | 8 | +| 27 | UINT32 | 1 | gemma4.attention.key_length | 512 | +| 28 | UINT32 | 1 | gemma4.attention.value_length | 512 | +| 29 | FLOAT32 | 1 | gemma4.final_logit_softcapping | 30.0 | +| 30 | UINT32 | 1 | gemma4.attention.sliding_window | 1024 | +| 31 | UINT32 | 1 | gemma4.attention.shared_kv_layers | 0 | +| 32 | UINT32 | 1 | gemma4.embedding_length_per_layer_input | 0 | +| 33 | [BOOL] | 30 | gemma4.attention.sliding_window_pattern | [ True, True, True, True, True, False, True, ... ] | +| 34 | UINT32 | 1 | gemma4.attention.key_length_swa | 256 | +| 35 | UINT32 | 1 | gemma4.attention.value_length_swa | 256 | +| 36 | UINT32 | 1 | gemma4.expert_feed_forward_length | 704 | +| 37 | UINT32 | 1 | gemma4.rope.dimension_count | 512 | +| 38 | UINT32 | 1 | gemma4.rope.dimension_count_swa | 256 | +| 39 | STRING | 1 | tokenizer.ggml.model | `gemma4` | +| 40 | [STRING] | 262144 | tokenizer.ggml.tokens | [ ``, ``, ``, ``, ``, ... ] | +| 41 | [FLOAT32] | 262144 | tokenizer.ggml.scores | [ -1000.0, -1000.0, -1000.0, -1000.0, -1000.0, -1000.0, -1000.0, ... ] | +| 42 | [INT32] | 262144 | tokenizer.ggml.token_type | [ 3, 3, 3, 3, 3, 1, 1, ... ] | +| 45 | [STRING] | 514906 | tokenizer.ggml.merges | [ ``...``, `▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁`...`▁▁▁▁▁▁▁▁▁▁▁▁▁ ▁`, ``...``, ``...``, `▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁`...`▁▁▁▁▁▁▁▁▁▁▁▁ ▁▁`, ... ] | +| 44 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 2 | +| 45 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 1 | +| 46 | UINT32 | 1 | tokenizer.ggml.unknown_token_id | 3 | +| 47 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 0 | +| 48 | UINT32 | 1 | tokenizer.ggml.mask_token_id | 4 | +| 49 | STRING | 1 | tokenizer.chat_template | `{%- macro format_parameters(pr`...` {%- endif -%} {%- endif -%}` | +| 50 | BOOL | 1 | tokenizer.ggml.add_space_prefix | False | +| 51 | BOOL | 1 | tokenizer.ggml.add_bos_token | True | +| 52 | UINT32 | 1 | general.quantization_version | 2 | +| 53 | UINT32 | 1 | general.file_type | 30 | +| 54 | STRING | 1 | quantize.imatrix.file | `gemma-4-26B-A4B-it-WIP/imatrix`...`gemma-4-26B-A4B-it-medium.gguf` | +| 55 | STRING | 1 | quantize.imatrix.dataset | `../datasets/imatrix/combined_eur_medium.txt` | +| 56 | UINT32 | 1 | quantize.imatrix.entries_count | 295 | +| 57 | UINT32 | 1 | quantize.imatrix.chunks_count | 2471 | + +## Tensors Overview ~25B Elements + +Total number of elements in all tensors: 25233142046 Elements + +- [/Users/ed/Development/AI/hf/gemma-4-26B-A4B-it-WIP/gemma-4-26B-A4B-it-Q3\_K.gguf - GGUF Internal File Dump](#userseddevelopmentaihfgemma-4-26b-a4b-it-wipgemma-4-26b-a4b-it-q3_kgguf---gguf-internal-file-dump) + - [Key Value Metadata Store](#key-value-metadata-store) + - [Tensors Overview ~25B Elements](#tensors-overview-25b-elements) + - [Tensor Data Offset](#tensor-data-offset) + - [Base Tensor Group : ~738M Elements](#base-tensor-group--738m-elements) + - [Block 0 Tensor Group : ~814M Elements](#block-0-tensor-group--814m-elements) + - [Block 1 Tensor Group : ~814M Elements](#block-1-tensor-group--814m-elements) + - [Block 2 Tensor Group : ~814M Elements](#block-2-tensor-group--814m-elements) + - [Block 3 Tensor Group : ~814M Elements](#block-3-tensor-group--814m-elements) + - [Block 4 Tensor Group : ~814M Elements](#block-4-tensor-group--814m-elements) + - [Block 5 Tensor Group : ~829M Elements](#block-5-tensor-group--829m-elements) + - [Block 6 Tensor Group : ~814M Elements](#block-6-tensor-group--814m-elements) + - [Block 7 Tensor Group : ~814M Elements](#block-7-tensor-group--814m-elements) + - [Block 8 Tensor Group : ~814M Elements](#block-8-tensor-group--814m-elements) + - [Block 9 Tensor Group : ~814M Elements](#block-9-tensor-group--814m-elements) + - [Block 10 Tensor Group : ~814M Elements](#block-10-tensor-group--814m-elements) + - [Block 11 Tensor Group : ~829M Elements](#block-11-tensor-group--829m-elements) + - [Block 12 Tensor Group : ~814M Elements](#block-12-tensor-group--814m-elements) + - [Block 13 Tensor Group : ~814M Elements](#block-13-tensor-group--814m-elements) + - [Block 14 Tensor Group : ~814M Elements](#block-14-tensor-group--814m-elements) + - [Block 15 Tensor Group : ~814M Elements](#block-15-tensor-group--814m-elements) + - [Block 16 Tensor Group : ~814M Elements](#block-16-tensor-group--814m-elements) + - [Block 17 Tensor Group : ~829M Elements](#block-17-tensor-group--829m-elements) + - [Block 18 Tensor Group : ~814M Elements](#block-18-tensor-group--814m-elements) + - [Block 19 Tensor Group : ~814M Elements](#block-19-tensor-group--814m-elements) + - [Block 20 Tensor Group : ~814M Elements](#block-20-tensor-group--814m-elements) + - [Block 21 Tensor Group : ~814M Elements](#block-21-tensor-group--814m-elements) + - [Block 22 Tensor Group : ~814M Elements](#block-22-tensor-group--814m-elements) + - [Block 23 Tensor Group : ~829M Elements](#block-23-tensor-group--829m-elements) + - [Block 24 Tensor Group : ~814M Elements](#block-24-tensor-group--814m-elements) + - [Block 25 Tensor Group : ~814M Elements](#block-25-tensor-group--814m-elements) + - [Block 26 Tensor Group : ~814M Elements](#block-26-tensor-group--814m-elements) + - [Block 27 Tensor Group : ~814M Elements](#block-27-tensor-group--814m-elements) + - [Block 28 Tensor Group : ~814M Elements](#block-28-tensor-group--814m-elements) + - [Block 29 Tensor Group : ~829M Elements](#block-29-tensor-group--829m-elements) + +### Tensor Data Offset + +This table contains the offset and data segment relative to start of file + +| T_ID | Tensor Layer Name | Data Offset (B) | Data Size (B) | +| ---: | :-------------------------------- | --------------: | ------------: | +| 0 | output_norm.weight | 0xf16c00 | 0x2c00 | +| 1 | rope_freqs.weight | 0xf19800 | 0x400 | +| 2 | token_embd.weight | 0xf19c00 | 0x12e80000 | +| 3 | blk.0.attn_k.weight | 0x13d99c00 | 0x21b000 | +| 4 | blk.0.attn_k_norm.weight | 0x13fb4c00 | 0x400 | +| 5 | blk.0.attn_norm.weight | 0x13fb5000 | 0x2c00 | +| 6 | blk.0.attn_output.weight | 0x13fb7c00 | 0x436000 | +| 7 | blk.0.attn_q.weight | 0x143edc00 | 0x436000 | +| 8 | blk.0.attn_q_norm.weight | 0x14823c00 | 0x400 | +| 9 | blk.0.attn_v.weight | 0x14824000 | 0x1ce000 | +| 10 | blk.0.ffn_down.weight | 0x149f2000 | 0x330c00 | +| 11 | blk.0.ffn_down_exps.scale | 0x14d22c00 | 0x200 | +| 12 | blk.0.ffn_down_exps.weight | 0x14d22e00 | 0x8820000 | +| 13 | blk.0.ffn_gate.weight | 0x1d542e00 | 0x1dc700 | +| 14 | blk.0.ffn_gate_inp.scale | 0x1d71f500 | 0x2c00 | +| 15 | blk.0.ffn_gate_inp.weight | 0x1d722100 | 0x160000 | +| 16 | blk.0.ffn_gate_up_exps.weight | 0x1d882100 | 0x9ed0000 | +| 17 | blk.0.ffn_norm.weight | 0x27752100 | 0x2c00 | +| 18 | blk.0.ffn_up.weight | 0x27754d00 | 0x1dc700 | +| 19 | blk.0.layer_output_scale.weight | 0x27931400 | 0x4 | +| 20 | blk.0.post_attention_norm.weight | 0x27931420 | 0x2c00 | +| 21 | blk.0.post_ffw_norm.weight | 0x27934020 | 0x2c00 | +| 22 | blk.0.post_ffw_norm_1.weight | 0x27936c20 | 0x2c00 | +| 23 | blk.0.post_ffw_norm_2.weight | 0x27939820 | 0x2c00 | +| 24 | blk.0.pre_ffw_norm_2.weight | 0x2793c420 | 0x2c00 | +| 25 | blk.1.attn_k.weight | 0x2793f020 | 0x21b000 | +| 26 | blk.1.attn_k_norm.weight | 0x27b5a020 | 0x400 | +| 27 | blk.1.attn_norm.weight | 0x27b5a420 | 0x2c00 | +| 28 | blk.1.attn_output.weight | 0x27b5d020 | 0x5d8000 | +| 29 | blk.1.attn_q.weight | 0x28135020 | 0x436000 | +| 30 | blk.1.attn_q_norm.weight | 0x2856b020 | 0x400 | +| 31 | blk.1.attn_v.weight | 0x2856b420 | 0x21b000 | +| 32 | blk.1.ffn_down.weight | 0x28786420 | 0x330c00 | +| 33 | blk.1.ffn_down_exps.scale | 0x28ab7020 | 0x200 | +| 34 | blk.1.ffn_down_exps.weight | 0x28ab7220 | 0x8820000 | +| 35 | blk.1.ffn_gate.weight | 0x312d7220 | 0x1dc700 | +| 36 | blk.1.ffn_gate_inp.scale | 0x314b3920 | 0x2c00 | +| 37 | blk.1.ffn_gate_inp.weight | 0x314b6520 | 0x160000 | +| 38 | blk.1.ffn_gate_up_exps.weight | 0x31616520 | 0xb948000 | +| 39 | blk.1.ffn_norm.weight | 0x3cf5e520 | 0x2c00 | +| 40 | blk.1.ffn_up.weight | 0x3cf61120 | 0x1dc700 | +| 41 | blk.1.layer_output_scale.weight | 0x3d13d820 | 0x4 | +| 42 | blk.1.post_attention_norm.weight | 0x3d13d840 | 0x2c00 | +| 43 | blk.1.post_ffw_norm.weight | 0x3d140440 | 0x2c00 | +| 44 | blk.1.post_ffw_norm_1.weight | 0x3d143040 | 0x2c00 | +| 45 | blk.1.post_ffw_norm_2.weight | 0x3d145c40 | 0x2c00 | +| 46 | blk.1.pre_ffw_norm_2.weight | 0x3d148840 | 0x2c00 | +| 47 | blk.2.attn_k.weight | 0x3d14b440 | 0x21b000 | +| 48 | blk.2.attn_k_norm.weight | 0x3d366440 | 0x400 | +| 49 | blk.2.attn_norm.weight | 0x3d366840 | 0x2c00 | +| 50 | blk.2.attn_output.weight | 0x3d369440 | 0x5d8000 | +| 51 | blk.2.attn_q.weight | 0x3d941440 | 0x436000 | +| 52 | blk.2.attn_q_norm.weight | 0x3dd77440 | 0x400 | +| 53 | blk.2.attn_v.weight | 0x3dd77840 | 0x2ec000 | +| 54 | blk.2.ffn_down.weight | 0x3e063840 | 0x330c00 | +| 55 | blk.2.ffn_down_exps.scale | 0x3e394440 | 0x200 | +| 56 | blk.2.ffn_down_exps.weight | 0x3e394640 | 0x8820000 | +| 57 | blk.2.ffn_gate.weight | 0x46bb4640 | 0x1dc700 | +| 58 | blk.2.ffn_gate_inp.scale | 0x46d90d40 | 0x2c00 | +| 59 | blk.2.ffn_gate_inp.weight | 0x46d93940 | 0x160000 | +| 60 | blk.2.ffn_gate_up_exps.weight | 0x46ef3940 | 0xb948000 | +| 61 | blk.2.ffn_norm.weight | 0x5283b940 | 0x2c00 | +| 62 | blk.2.ffn_up.weight | 0x5283e540 | 0x1dc700 | +| 63 | blk.2.layer_output_scale.weight | 0x52a1ac40 | 0x4 | +| 64 | blk.2.post_attention_norm.weight | 0x52a1ac60 | 0x2c00 | +| 65 | blk.2.post_ffw_norm.weight | 0x52a1d860 | 0x2c00 | +| 66 | blk.2.post_ffw_norm_1.weight | 0x52a20460 | 0x2c00 | +| 67 | blk.2.post_ffw_norm_2.weight | 0x52a23060 | 0x2c00 | +| 68 | blk.2.pre_ffw_norm_2.weight | 0x52a25c60 | 0x2c00 | +| 69 | blk.3.attn_k.weight | 0x52a28860 | 0x21b000 | +| 70 | blk.3.attn_k_norm.weight | 0x52c43860 | 0x400 | +| 71 | blk.3.attn_norm.weight | 0x52c43c60 | 0x2c00 | +| 72 | blk.3.attn_output.weight | 0x52c46860 | 0x5d8000 | +| 73 | blk.3.attn_q.weight | 0x5321e860 | 0x436000 | +| 74 | blk.3.attn_q_norm.weight | 0x53654860 | 0x400 | +| 75 | blk.3.attn_v.weight | 0x53654c60 | 0x21b000 | +| 76 | blk.3.ffn_down.weight | 0x5386fc60 | 0x330c00 | +| 77 | blk.3.ffn_down_exps.scale | 0x53ba0860 | 0x200 | +| 78 | blk.3.ffn_down_exps.weight | 0x53ba0a60 | 0x8820000 | +| 79 | blk.3.ffn_gate.weight | 0x5c3c0a60 | 0x1dc700 | +| 80 | blk.3.ffn_gate_inp.scale | 0x5c59d160 | 0x2c00 | +| 81 | blk.3.ffn_gate_inp.weight | 0x5c59fd60 | 0x160000 | +| 82 | blk.3.ffn_gate_up_exps.weight | 0x5c6ffd60 | 0xb948000 | +| 83 | blk.3.ffn_norm.weight | 0x68047d60 | 0x2c00 | +| 84 | blk.3.ffn_up.weight | 0x6804a960 | 0x22bd80 | +| 85 | blk.3.layer_output_scale.weight | 0x682766e0 | 0x4 | +| 86 | blk.3.post_attention_norm.weight | 0x68276700 | 0x2c00 | +| 87 | blk.3.post_ffw_norm.weight | 0x68279300 | 0x2c00 | +| 88 | blk.3.post_ffw_norm_1.weight | 0x6827bf00 | 0x2c00 | +| 89 | blk.3.post_ffw_norm_2.weight | 0x6827eb00 | 0x2c00 | +| 90 | blk.3.pre_ffw_norm_2.weight | 0x68281700 | 0x2c00 | +| 91 | blk.4.attn_k.weight | 0x68284300 | 0x21b000 | +| 92 | blk.4.attn_k_norm.weight | 0x6849f300 | 0x400 | +| 93 | blk.4.attn_norm.weight | 0x6849f700 | 0x2c00 | +| 94 | blk.4.attn_output.weight | 0x684a2300 | 0x5d8000 | +| 95 | blk.4.attn_q.weight | 0x68a7a300 | 0x436000 | +| 96 | blk.4.attn_q_norm.weight | 0x68eb0300 | 0x400 | +| 97 | blk.4.attn_v.weight | 0x68eb0700 | 0x2ec000 | +| 98 | blk.4.ffn_down.weight | 0x6919c700 | 0x330c00 | +| 99 | blk.4.ffn_down_exps.scale | 0x694cd300 | 0x200 | +| 100 | blk.4.ffn_down_exps.weight | 0x694cd500 | 0x8820000 | +| 101 | blk.4.ffn_gate.weight | 0x71ced500 | 0x1dc700 | +| 102 | blk.4.ffn_gate_inp.scale | 0x71ec9c00 | 0x2c00 | +| 103 | blk.4.ffn_gate_inp.weight | 0x71ecc800 | 0x160000 | +| 104 | blk.4.ffn_gate_up_exps.weight | 0x7202c800 | 0x9ed0000 | +| 105 | blk.4.ffn_norm.weight | 0x7befc800 | 0x2c00 | +| 106 | blk.4.ffn_up.weight | 0x7beff400 | 0x1dc700 | +| 107 | blk.4.layer_output_scale.weight | 0x7c0dbb00 | 0x4 | +| 108 | blk.4.post_attention_norm.weight | 0x7c0dbb20 | 0x2c00 | +| 109 | blk.4.post_ffw_norm.weight | 0x7c0de720 | 0x2c00 | +| 110 | blk.4.post_ffw_norm_1.weight | 0x7c0e1320 | 0x2c00 | +| 111 | blk.4.post_ffw_norm_2.weight | 0x7c0e3f20 | 0x2c00 | +| 112 | blk.4.pre_ffw_norm_2.weight | 0x7c0e6b20 | 0x2c00 | +| 113 | blk.5.attn_k.weight | 0x7c0e9720 | 0x10d800 | +| 114 | blk.5.attn_k_norm.weight | 0x7c1f6f20 | 0x800 | +| 115 | blk.5.attn_norm.weight | 0x7c1f7720 | 0x2c00 | +| 116 | blk.5.attn_output.weight | 0x7c1fa320 | 0x86c000 | +| 117 | blk.5.attn_q.weight | 0x7ca66320 | 0x86c000 | +| 118 | blk.5.attn_q_norm.weight | 0x7d2d2320 | 0x800 | +| 119 | blk.5.ffn_down.weight | 0x7d2d2b20 | 0x330c00 | +| 120 | blk.5.ffn_down_exps.scale | 0x7d603720 | 0x200 | +| 121 | blk.5.ffn_down_exps.weight | 0x7d603920 | 0x8820000 | +| 122 | blk.5.ffn_gate.weight | 0x85e23920 | 0x1dc700 | +| 123 | blk.5.ffn_gate_inp.scale | 0x86000020 | 0x2c00 | +| 124 | blk.5.ffn_gate_inp.weight | 0x86002c20 | 0x160000 | +| 125 | blk.5.ffn_gate_up_exps.weight | 0x86162c20 | 0x9ed0000 | +| 126 | blk.5.ffn_norm.weight | 0x90032c20 | 0x2c00 | +| 127 | blk.5.ffn_up.weight | 0x90035820 | 0x22bd80 | +| 128 | blk.5.layer_output_scale.weight | 0x902615a0 | 0x4 | +| 129 | blk.5.post_attention_norm.weight | 0x902615c0 | 0x2c00 | +| 130 | blk.5.post_ffw_norm.weight | 0x902641c0 | 0x2c00 | +| 131 | blk.5.post_ffw_norm_1.weight | 0x90266dc0 | 0x2c00 | +| 132 | blk.5.post_ffw_norm_2.weight | 0x902699c0 | 0x2c00 | +| 133 | blk.5.pre_ffw_norm_2.weight | 0x9026c5c0 | 0x2c00 | +| 134 | blk.6.attn_k.weight | 0x9026f1c0 | 0x21b000 | +| 135 | blk.6.attn_k_norm.weight | 0x9048a1c0 | 0x400 | +| 136 | blk.6.attn_norm.weight | 0x9048a5c0 | 0x2c00 | +| 137 | blk.6.attn_output.weight | 0x9048d1c0 | 0x4ba000 | +| 138 | blk.6.attn_q.weight | 0x909471c0 | 0x436000 | +| 139 | blk.6.attn_q_norm.weight | 0x90d7d1c0 | 0x400 | +| 140 | blk.6.attn_v.weight | 0x90d7d5c0 | 0x21b000 | +| 141 | blk.6.ffn_down.weight | 0x90f985c0 | 0x330c00 | +| 142 | blk.6.ffn_down_exps.scale | 0x912c91c0 | 0x200 | +| 143 | blk.6.ffn_down_exps.weight | 0x912c93c0 | 0x8820000 | +| 144 | blk.6.ffn_gate.weight | 0x99ae93c0 | 0x1dc700 | +| 145 | blk.6.ffn_gate_inp.scale | 0x99cc5ac0 | 0x2c00 | +| 146 | blk.6.ffn_gate_inp.weight | 0x99cc86c0 | 0x160000 | +| 147 | blk.6.ffn_gate_up_exps.weight | 0x99e286c0 | 0x9ed0000 | +| 148 | blk.6.ffn_norm.weight | 0xa3cf86c0 | 0x2c00 | +| 149 | blk.6.ffn_up.weight | 0xa3cfb2c0 | 0x1dc700 | +| 150 | blk.6.layer_output_scale.weight | 0xa3ed79c0 | 0x4 | +| 151 | blk.6.post_attention_norm.weight | 0xa3ed79e0 | 0x2c00 | +| 152 | blk.6.post_ffw_norm.weight | 0xa3eda5e0 | 0x2c00 | +| 153 | blk.6.post_ffw_norm_1.weight | 0xa3edd1e0 | 0x2c00 | +| 154 | blk.6.post_ffw_norm_2.weight | 0xa3edfde0 | 0x2c00 | +| 155 | blk.6.pre_ffw_norm_2.weight | 0xa3ee29e0 | 0x2c00 | +| 156 | blk.7.attn_k.weight | 0xa3ee55e0 | 0x21b000 | +| 157 | blk.7.attn_k_norm.weight | 0xa41005e0 | 0x400 | +| 158 | blk.7.attn_norm.weight | 0xa41009e0 | 0x2c00 | +| 159 | blk.7.attn_output.weight | 0xa41035e0 | 0x5d8000 | +| 160 | blk.7.attn_q.weight | 0xa46db5e0 | 0x436000 | +| 161 | blk.7.attn_q_norm.weight | 0xa4b115e0 | 0x400 | +| 162 | blk.7.attn_v.weight | 0xa4b119e0 | 0x21b000 | +| 163 | blk.7.ffn_down.weight | 0xa4d2c9e0 | 0x330c00 | +| 164 | blk.7.ffn_down_exps.scale | 0xa505d5e0 | 0x200 | +| 165 | blk.7.ffn_down_exps.weight | 0xa505d7e0 | 0x8820000 | +| 166 | blk.7.ffn_gate.weight | 0xad87d7e0 | 0x1dc700 | +| 167 | blk.7.ffn_gate_inp.scale | 0xada59ee0 | 0x2c00 | +| 168 | blk.7.ffn_gate_inp.weight | 0xada5cae0 | 0x160000 | +| 169 | blk.7.ffn_gate_up_exps.weight | 0xadbbcae0 | 0xb948000 | +| 170 | blk.7.ffn_norm.weight | 0xb9504ae0 | 0x2c00 | +| 171 | blk.7.ffn_up.weight | 0xb95076e0 | 0x1dc700 | +| 172 | blk.7.layer_output_scale.weight | 0xb96e3de0 | 0x4 | +| 173 | blk.7.post_attention_norm.weight | 0xb96e3e00 | 0x2c00 | +| 174 | blk.7.post_ffw_norm.weight | 0xb96e6a00 | 0x2c00 | +| 175 | blk.7.post_ffw_norm_1.weight | 0xb96e9600 | 0x2c00 | +| 176 | blk.7.post_ffw_norm_2.weight | 0xb96ec200 | 0x2c00 | +| 177 | blk.7.pre_ffw_norm_2.weight | 0xb96eee00 | 0x2c00 | +| 178 | blk.8.attn_k.weight | 0xb96f1a00 | 0x21b000 | +| 179 | blk.8.attn_k_norm.weight | 0xb990ca00 | 0x400 | +| 180 | blk.8.attn_norm.weight | 0xb990ce00 | 0x2c00 | +| 181 | blk.8.attn_output.weight | 0xb990fa00 | 0x5d8000 | +| 182 | blk.8.attn_q.weight | 0xb9ee7a00 | 0x436000 | +| 183 | blk.8.attn_q_norm.weight | 0xba31da00 | 0x400 | +| 184 | blk.8.attn_v.weight | 0xba31de00 | 0x21b000 | +| 185 | blk.8.ffn_down.weight | 0xba538e00 | 0x330c00 | +| 186 | blk.8.ffn_down_exps.scale | 0xba869a00 | 0x200 | +| 187 | blk.8.ffn_down_exps.weight | 0xba869c00 | 0x8820000 | +| 188 | blk.8.ffn_gate.weight | 0xc3089c00 | 0x1dc700 | +| 189 | blk.8.ffn_gate_inp.scale | 0xc3266300 | 0x2c00 | +| 190 | blk.8.ffn_gate_inp.weight | 0xc3268f00 | 0x160000 | +| 191 | blk.8.ffn_gate_up_exps.weight | 0xc33c8f00 | 0xb948000 | +| 192 | blk.8.ffn_norm.weight | 0xced10f00 | 0x2c00 | +| 193 | blk.8.ffn_up.weight | 0xced13b00 | 0x1dc700 | +| 194 | blk.8.layer_output_scale.weight | 0xceef0200 | 0x4 | +| 195 | blk.8.post_attention_norm.weight | 0xceef0220 | 0x2c00 | +| 196 | blk.8.post_ffw_norm.weight | 0xceef2e20 | 0x2c00 | +| 197 | blk.8.post_ffw_norm_1.weight | 0xceef5a20 | 0x2c00 | +| 198 | blk.8.post_ffw_norm_2.weight | 0xceef8620 | 0x2c00 | +| 199 | blk.8.pre_ffw_norm_2.weight | 0xceefb220 | 0x2c00 | +| 200 | blk.9.attn_k.weight | 0xceefde20 | 0x21b000 | +| 201 | blk.9.attn_k_norm.weight | 0xcf118e20 | 0x400 | +| 202 | blk.9.attn_norm.weight | 0xcf119220 | 0x2c00 | +| 203 | blk.9.attn_output.weight | 0xcf11be20 | 0x5d8000 | +| 204 | blk.9.attn_q.weight | 0xcf6f3e20 | 0x436000 | +| 205 | blk.9.attn_q_norm.weight | 0xcfb29e20 | 0x400 | +| 206 | blk.9.attn_v.weight | 0xcfb2a220 | 0x2ec000 | +| 207 | blk.9.ffn_down.weight | 0xcfe16220 | 0x330c00 | +| 208 | blk.9.ffn_down_exps.scale | 0xd0146e20 | 0x200 | +| 209 | blk.9.ffn_down_exps.weight | 0xd0147020 | 0x8820000 | +| 210 | blk.9.ffn_gate.weight | 0xd8967020 | 0x22bd80 | +| 211 | blk.9.ffn_gate_inp.scale | 0xd8b92da0 | 0x2c00 | +| 212 | blk.9.ffn_gate_inp.weight | 0xd8b959a0 | 0x160000 | +| 213 | blk.9.ffn_gate_up_exps.weight | 0xd8cf59a0 | 0xb948000 | +| 214 | blk.9.ffn_norm.weight | 0xe463d9a0 | 0x2c00 | +| 215 | blk.9.ffn_up.weight | 0xe46405a0 | 0x22bd80 | +| 216 | blk.9.layer_output_scale.weight | 0xe486c320 | 0x4 | +| 217 | blk.9.post_attention_norm.weight | 0xe486c340 | 0x2c00 | +| 218 | blk.9.post_ffw_norm.weight | 0xe486ef40 | 0x2c00 | +| 219 | blk.9.post_ffw_norm_1.weight | 0xe4871b40 | 0x2c00 | +| 220 | blk.9.post_ffw_norm_2.weight | 0xe4874740 | 0x2c00 | +| 221 | blk.9.pre_ffw_norm_2.weight | 0xe4877340 | 0x2c00 | +| 222 | blk.10.attn_k.weight | 0xe4879f40 | 0x21b000 | +| 223 | blk.10.attn_k_norm.weight | 0xe4a94f40 | 0x400 | +| 224 | blk.10.attn_norm.weight | 0xe4a95340 | 0x2c00 | +| 225 | blk.10.attn_output.weight | 0xe4a97f40 | 0x5d8000 | +| 226 | blk.10.attn_q.weight | 0xe506ff40 | 0x436000 | +| 227 | blk.10.attn_q_norm.weight | 0xe54a5f40 | 0x400 | +| 228 | blk.10.attn_v.weight | 0xe54a6340 | 0x2ec000 | +| 229 | blk.10.ffn_down.weight | 0xe5792340 | 0x330c00 | +| 230 | blk.10.ffn_down_exps.scale | 0xe5ac2f40 | 0x200 | +| 231 | blk.10.ffn_down_exps.weight | 0xe5ac3140 | 0x8820000 | +| 232 | blk.10.ffn_gate.weight | 0xee2e3140 | 0x22bd80 | +| 233 | blk.10.ffn_gate_inp.scale | 0xee50eec0 | 0x2c00 | +| 234 | blk.10.ffn_gate_inp.weight | 0xee511ac0 | 0x160000 | +| 235 | blk.10.ffn_gate_up_exps.weight | 0xee671ac0 | 0x9ed0000 | +| 236 | blk.10.ffn_norm.weight | 0xf8541ac0 | 0x2c00 | +| 237 | blk.10.ffn_up.weight | 0xf85446c0 | 0x22bd80 | +| 238 | blk.10.layer_output_scale.weight | 0xf8770440 | 0x4 | +| 239 | blk.10.post_attention_norm.weight | 0xf8770460 | 0x2c00 | +| 240 | blk.10.post_ffw_norm.weight | 0xf8773060 | 0x2c00 | +| 241 | blk.10.post_ffw_norm_1.weight | 0xf8775c60 | 0x2c00 | +| 242 | blk.10.post_ffw_norm_2.weight | 0xf8778860 | 0x2c00 | +| 243 | blk.10.pre_ffw_norm_2.weight | 0xf877b460 | 0x2c00 | +| 244 | blk.11.attn_k.weight | 0xf877e060 | 0x10d800 | +| 245 | blk.11.attn_k_norm.weight | 0xf888b860 | 0x800 | +| 246 | blk.11.attn_norm.weight | 0xf888c060 | 0x2c00 | +| 247 | blk.11.attn_output.weight | 0xf888ec60 | 0x86c000 | +| 248 | blk.11.attn_q.weight | 0xf90fac60 | 0x86c000 | +| 249 | blk.11.attn_q_norm.weight | 0xf9966c60 | 0x800 | +| 250 | blk.11.ffn_down.weight | 0xf9967460 | 0x330c00 | +| 251 | blk.11.ffn_down_exps.scale | 0xf9c98060 | 0x200 | +| 252 | blk.11.ffn_down_exps.weight | 0xf9c98260 | 0x8820000 | +| 253 | blk.11.ffn_gate.weight | 0x1024b8260 | 0x22bd80 | +| 254 | blk.11.ffn_gate_inp.scale | 0x1026e3fe0 | 0x2c00 | +| 255 | blk.11.ffn_gate_inp.weight | 0x1026e6be0 | 0x160000 | +| 256 | blk.11.ffn_gate_up_exps.weight | 0x102846be0 | 0xb948000 | +| 257 | blk.11.ffn_norm.weight | 0x10e18ebe0 | 0x2c00 | +| 258 | blk.11.ffn_up.weight | 0x10e1917e0 | 0x22bd80 | +| 259 | blk.11.layer_output_scale.weight | 0x10e3bd560 | 0x4 | +| 260 | blk.11.post_attention_norm.weight | 0x10e3bd580 | 0x2c00 | +| 261 | blk.11.post_ffw_norm.weight | 0x10e3c0180 | 0x2c00 | +| 262 | blk.11.post_ffw_norm_1.weight | 0x10e3c2d80 | 0x2c00 | +| 263 | blk.11.post_ffw_norm_2.weight | 0x10e3c5980 | 0x2c00 | +| 264 | blk.11.pre_ffw_norm_2.weight | 0x10e3c8580 | 0x2c00 | +| 265 | blk.12.attn_k.weight | 0x10e3cb180 | 0x21b000 | +| 266 | blk.12.attn_k_norm.weight | 0x10e5e6180 | 0x400 | +| 267 | blk.12.attn_norm.weight | 0x10e5e6580 | 0x2c00 | +| 268 | blk.12.attn_output.weight | 0x10e5e9180 | 0x436000 | +| 269 | blk.12.attn_q.weight | 0x10ea1f180 | 0x436000 | +| 270 | blk.12.attn_q_norm.weight | 0x10ee55180 | 0x400 | +| 271 | blk.12.attn_v.weight | 0x10ee55580 | 0x21b000 | +| 272 | blk.12.ffn_down.weight | 0x10f070580 | 0x330c00 | +| 273 | blk.12.ffn_down_exps.scale | 0x10f3a1180 | 0x200 | +| 274 | blk.12.ffn_down_exps.weight | 0x10f3a1380 | 0x8820000 | +| 275 | blk.12.ffn_gate.weight | 0x117bc1380 | 0x22bd80 | +| 276 | blk.12.ffn_gate_inp.scale | 0x117ded100 | 0x2c00 | +| 277 | blk.12.ffn_gate_inp.weight | 0x117defd00 | 0x160000 | +| 278 | blk.12.ffn_gate_up_exps.weight | 0x117f4fd00 | 0xb948000 | +| 279 | blk.12.ffn_norm.weight | 0x123897d00 | 0x2c00 | +| 280 | blk.12.ffn_up.weight | 0x12389a900 | 0x22bd80 | +| 281 | blk.12.layer_output_scale.weight | 0x123ac6680 | 0x4 | +| 282 | blk.12.post_attention_norm.weight | 0x123ac66a0 | 0x2c00 | +| 283 | blk.12.post_ffw_norm.weight | 0x123ac92a0 | 0x2c00 | +| 284 | blk.12.post_ffw_norm_1.weight | 0x123acbea0 | 0x2c00 | +| 285 | blk.12.post_ffw_norm_2.weight | 0x123aceaa0 | 0x2c00 | +| 286 | blk.12.pre_ffw_norm_2.weight | 0x123ad16a0 | 0x2c00 | +| 287 | blk.13.attn_k.weight | 0x123ad42a0 | 0x21b000 | +| 288 | blk.13.attn_k_norm.weight | 0x123cef2a0 | 0x400 | +| 289 | blk.13.attn_norm.weight | 0x123cef6a0 | 0x2c00 | +| 290 | blk.13.attn_output.weight | 0x123cf22a0 | 0x5d8000 | +| 291 | blk.13.attn_q.weight | 0x1242ca2a0 | 0x436000 | +| 292 | blk.13.attn_q_norm.weight | 0x1247002a0 | 0x400 | +| 293 | blk.13.attn_v.weight | 0x1247006a0 | 0x2ec000 | +| 294 | blk.13.ffn_down.weight | 0x1249ec6a0 | 0x330c00 | +| 295 | blk.13.ffn_down_exps.scale | 0x124d1d2a0 | 0x200 | +| 296 | blk.13.ffn_down_exps.weight | 0x124d1d4a0 | 0x8820000 | +| 297 | blk.13.ffn_gate.weight | 0x12d53d4a0 | 0x22bd80 | +| 298 | blk.13.ffn_gate_inp.scale | 0x12d769220 | 0x2c00 | +| 299 | blk.13.ffn_gate_inp.weight | 0x12d76be20 | 0x160000 | +| 300 | blk.13.ffn_gate_up_exps.weight | 0x12d8cbe20 | 0xb948000 | +| 301 | blk.13.ffn_norm.weight | 0x139213e20 | 0x2c00 | +| 302 | blk.13.ffn_up.weight | 0x139216a20 | 0x22bd80 | +| 303 | blk.13.layer_output_scale.weight | 0x1394427a0 | 0x4 | +| 304 | blk.13.post_attention_norm.weight | 0x1394427c0 | 0x2c00 | +| 305 | blk.13.post_ffw_norm.weight | 0x1394453c0 | 0x2c00 | +| 306 | blk.13.post_ffw_norm_1.weight | 0x139447fc0 | 0x2c00 | +| 307 | blk.13.post_ffw_norm_2.weight | 0x13944abc0 | 0x2c00 | +| 308 | blk.13.pre_ffw_norm_2.weight | 0x13944d7c0 | 0x2c00 | +| 309 | blk.14.attn_k.weight | 0x1394503c0 | 0x21b000 | +| 310 | blk.14.attn_k_norm.weight | 0x13966b3c0 | 0x400 | +| 311 | blk.14.attn_norm.weight | 0x13966b7c0 | 0x2c00 | +| 312 | blk.14.attn_output.weight | 0x13966e3c0 | 0x5d8000 | +| 313 | blk.14.attn_q.weight | 0x139c463c0 | 0x436000 | +| 314 | blk.14.attn_q_norm.weight | 0x13a07c3c0 | 0x400 | +| 315 | blk.14.attn_v.weight | 0x13a07c7c0 | 0x21b000 | +| 316 | blk.14.ffn_down.weight | 0x13a2977c0 | 0x330c00 | +| 317 | blk.14.ffn_down_exps.scale | 0x13a5c83c0 | 0x200 | +| 318 | blk.14.ffn_down_exps.weight | 0x13a5c85c0 | 0x8820000 | +| 319 | blk.14.ffn_gate.weight | 0x142de85c0 | 0x22bd80 | +| 320 | blk.14.ffn_gate_inp.scale | 0x143014340 | 0x2c00 | +| 321 | blk.14.ffn_gate_inp.weight | 0x143016f40 | 0x160000 | +| 322 | blk.14.ffn_gate_up_exps.weight | 0x143176f40 | 0xb948000 | +| 323 | blk.14.ffn_norm.weight | 0x14eabef40 | 0x2c00 | +| 324 | blk.14.ffn_up.weight | 0x14eac1b40 | 0x22bd80 | +| 325 | blk.14.layer_output_scale.weight | 0x14eced8c0 | 0x4 | +| 326 | blk.14.post_attention_norm.weight | 0x14eced8e0 | 0x2c00 | +| 327 | blk.14.post_ffw_norm.weight | 0x14ecf04e0 | 0x2c00 | +| 328 | blk.14.post_ffw_norm_1.weight | 0x14ecf30e0 | 0x2c00 | +| 329 | blk.14.post_ffw_norm_2.weight | 0x14ecf5ce0 | 0x2c00 | +| 330 | blk.14.pre_ffw_norm_2.weight | 0x14ecf88e0 | 0x2c00 | +| 331 | blk.15.attn_k.weight | 0x14ecfb4e0 | 0x21b000 | +| 332 | blk.15.attn_k_norm.weight | 0x14ef164e0 | 0x400 | +| 333 | blk.15.attn_norm.weight | 0x14ef168e0 | 0x2c00 | +| 334 | blk.15.attn_output.weight | 0x14ef194e0 | 0x5d8000 | +| 335 | blk.15.attn_q.weight | 0x14f4f14e0 | 0x436000 | +| 336 | blk.15.attn_q_norm.weight | 0x14f9274e0 | 0x400 | +| 337 | blk.15.attn_v.weight | 0x14f9278e0 | 0x2ec000 | +| 338 | blk.15.ffn_down.weight | 0x14fc138e0 | 0x330c00 | +| 339 | blk.15.ffn_down_exps.scale | 0x14ff444e0 | 0x200 | +| 340 | blk.15.ffn_down_exps.weight | 0x14ff446e0 | 0x8820000 | +| 341 | blk.15.ffn_gate.weight | 0x1587646e0 | 0x22bd80 | +| 342 | blk.15.ffn_gate_inp.scale | 0x158990460 | 0x2c00 | +| 343 | blk.15.ffn_gate_inp.weight | 0x158993060 | 0x160000 | +| 344 | blk.15.ffn_gate_up_exps.weight | 0x158af3060 | 0xb948000 | +| 345 | blk.15.ffn_norm.weight | 0x16443b060 | 0x2c00 | +| 346 | blk.15.ffn_up.weight | 0x16443dc60 | 0x22bd80 | +| 347 | blk.15.layer_output_scale.weight | 0x1646699e0 | 0x4 | +| 348 | blk.15.post_attention_norm.weight | 0x164669a00 | 0x2c00 | +| 349 | blk.15.post_ffw_norm.weight | 0x16466c600 | 0x2c00 | +| 350 | blk.15.post_ffw_norm_1.weight | 0x16466f200 | 0x2c00 | +| 351 | blk.15.post_ffw_norm_2.weight | 0x164671e00 | 0x2c00 | +| 352 | blk.15.pre_ffw_norm_2.weight | 0x164674a00 | 0x2c00 | +| 353 | blk.16.attn_k.weight | 0x164677600 | 0x21b000 | +| 354 | blk.16.attn_k_norm.weight | 0x164892600 | 0x400 | +| 355 | blk.16.attn_norm.weight | 0x164892a00 | 0x2c00 | +| 356 | blk.16.attn_output.weight | 0x164895600 | 0x5d8000 | +| 357 | blk.16.attn_q.weight | 0x164e6d600 | 0x436000 | +| 358 | blk.16.attn_q_norm.weight | 0x1652a3600 | 0x400 | +| 359 | blk.16.attn_v.weight | 0x1652a3a00 | 0x2ec000 | +| 360 | blk.16.ffn_down.weight | 0x16558fa00 | 0x330c00 | +| 361 | blk.16.ffn_down_exps.scale | 0x1658c0600 | 0x200 | +| 362 | blk.16.ffn_down_exps.weight | 0x1658c0800 | 0x8820000 | +| 363 | blk.16.ffn_gate.weight | 0x16e0e0800 | 0x22bd80 | +| 364 | blk.16.ffn_gate_inp.scale | 0x16e30c580 | 0x2c00 | +| 365 | blk.16.ffn_gate_inp.weight | 0x16e30f180 | 0x160000 | +| 366 | blk.16.ffn_gate_up_exps.weight | 0x16e46f180 | 0xb948000 | +| 367 | blk.16.ffn_norm.weight | 0x179db7180 | 0x2c00 | +| 368 | blk.16.ffn_up.weight | 0x179db9d80 | 0x22bd80 | +| 369 | blk.16.layer_output_scale.weight | 0x179fe5b00 | 0x4 | +| 370 | blk.16.post_attention_norm.weight | 0x179fe5b20 | 0x2c00 | +| 371 | blk.16.post_ffw_norm.weight | 0x179fe8720 | 0x2c00 | +| 372 | blk.16.post_ffw_norm_1.weight | 0x179feb320 | 0x2c00 | +| 373 | blk.16.post_ffw_norm_2.weight | 0x179fedf20 | 0x2c00 | +| 374 | blk.16.pre_ffw_norm_2.weight | 0x179ff0b20 | 0x2c00 | +| 375 | blk.17.attn_k.weight | 0x179ff3720 | 0x12e800 | +| 376 | blk.17.attn_k_norm.weight | 0x17a121f20 | 0x800 | +| 377 | blk.17.attn_norm.weight | 0x17a122720 | 0x2c00 | +| 378 | blk.17.attn_output.weight | 0x17a125320 | 0x86c000 | +| 379 | blk.17.attn_q.weight | 0x17a991320 | 0x974000 | +| 380 | blk.17.attn_q_norm.weight | 0x17b305320 | 0x800 | +| 381 | blk.17.ffn_down.weight | 0x17b305b20 | 0x330c00 | +| 382 | blk.17.ffn_down_exps.scale | 0x17b636720 | 0x200 | +| 383 | blk.17.ffn_down_exps.weight | 0x17b636920 | 0x8820000 | +| 384 | blk.17.ffn_gate.weight | 0x183e56920 | 0x22bd80 | +| 385 | blk.17.ffn_gate_inp.scale | 0x1840826a0 | 0x2c00 | +| 386 | blk.17.ffn_gate_inp.weight | 0x1840852a0 | 0x160000 | +| 387 | blk.17.ffn_gate_up_exps.weight | 0x1841e52a0 | 0xb948000 | +| 388 | blk.17.ffn_norm.weight | 0x18fb2d2a0 | 0x2c00 | +| 389 | blk.17.ffn_up.weight | 0x18fb2fea0 | 0x22bd80 | +| 390 | blk.17.layer_output_scale.weight | 0x18fd5bc20 | 0x4 | +| 391 | blk.17.post_attention_norm.weight | 0x18fd5bc40 | 0x2c00 | +| 392 | blk.17.post_ffw_norm.weight | 0x18fd5e840 | 0x2c00 | +| 393 | blk.17.post_ffw_norm_1.weight | 0x18fd61440 | 0x2c00 | +| 394 | blk.17.post_ffw_norm_2.weight | 0x18fd64040 | 0x2c00 | +| 395 | blk.17.pre_ffw_norm_2.weight | 0x18fd66c40 | 0x2c00 | +| 396 | blk.18.attn_k.weight | 0x18fd69840 | 0x21b000 | +| 397 | blk.18.attn_k_norm.weight | 0x18ff84840 | 0x400 | +| 398 | blk.18.attn_norm.weight | 0x18ff84c40 | 0x2c00 | +| 399 | blk.18.attn_output.weight | 0x18ff87840 | 0x4ba000 | +| 400 | blk.18.attn_q.weight | 0x190441840 | 0x4ba000 | +| 401 | blk.18.attn_q_norm.weight | 0x1908fb840 | 0x400 | +| 402 | blk.18.attn_v.weight | 0x1908fbc40 | 0x21b000 | +| 403 | blk.18.ffn_down.weight | 0x190b16c40 | 0x330c00 | +| 404 | blk.18.ffn_down_exps.scale | 0x190e47840 | 0x200 | +| 405 | blk.18.ffn_down_exps.weight | 0x190e47a40 | 0x8820000 | +| 406 | blk.18.ffn_gate.weight | 0x199667a40 | 0x22bd80 | +| 407 | blk.18.ffn_gate_inp.scale | 0x1998937c0 | 0x2c00 | +| 408 | blk.18.ffn_gate_inp.weight | 0x1998963c0 | 0x160000 | +| 409 | blk.18.ffn_gate_up_exps.weight | 0x1999f63c0 | 0xb948000 | +| 410 | blk.18.ffn_norm.weight | 0x1a533e3c0 | 0x2c00 | +| 411 | blk.18.ffn_up.weight | 0x1a5340fc0 | 0x303600 | +| 412 | blk.18.layer_output_scale.weight | 0x1a56445c0 | 0x4 | +| 413 | blk.18.post_attention_norm.weight | 0x1a56445e0 | 0x2c00 | +| 414 | blk.18.post_ffw_norm.weight | 0x1a56471e0 | 0x2c00 | +| 415 | blk.18.post_ffw_norm_1.weight | 0x1a5649de0 | 0x2c00 | +| 416 | blk.18.post_ffw_norm_2.weight | 0x1a564c9e0 | 0x2c00 | +| 417 | blk.18.pre_ffw_norm_2.weight | 0x1a564f5e0 | 0x2c00 | +| 418 | blk.19.attn_k.weight | 0x1a56521e0 | 0x21b000 | +| 419 | blk.19.attn_k_norm.weight | 0x1a586d1e0 | 0x400 | +| 420 | blk.19.attn_norm.weight | 0x1a586d5e0 | 0x2c00 | +| 421 | blk.19.attn_output.weight | 0x1a58701e0 | 0x5d8000 | +| 422 | blk.19.attn_q.weight | 0x1a5e481e0 | 0x4ba000 | +| 423 | blk.19.attn_q_norm.weight | 0x1a63021e0 | 0x400 | +| 424 | blk.19.attn_v.weight | 0x1a63025e0 | 0x2ec000 | +| 425 | blk.19.ffn_down.weight | 0x1a65ee5e0 | 0x330c00 | +| 426 | blk.19.ffn_down_exps.scale | 0x1a691f1e0 | 0x200 | +| 427 | blk.19.ffn_down_exps.weight | 0x1a691f3e0 | 0x8820000 | +| 428 | blk.19.ffn_gate.weight | 0x1af13f3e0 | 0x22bd80 | +| 429 | blk.19.ffn_gate_inp.scale | 0x1af36b160 | 0x2c00 | +| 430 | blk.19.ffn_gate_inp.weight | 0x1af36dd60 | 0x160000 | +| 431 | blk.19.ffn_gate_up_exps.weight | 0x1af4cdd60 | 0xb948000 | +| 432 | blk.19.ffn_norm.weight | 0x1bae15d60 | 0x2c00 | +| 433 | blk.19.ffn_up.weight | 0x1bae18960 | 0x22bd80 | +| 434 | blk.19.layer_output_scale.weight | 0x1bb0446e0 | 0x4 | +| 435 | blk.19.post_attention_norm.weight | 0x1bb044700 | 0x2c00 | +| 436 | blk.19.post_ffw_norm.weight | 0x1bb047300 | 0x2c00 | +| 437 | blk.19.post_ffw_norm_1.weight | 0x1bb049f00 | 0x2c00 | +| 438 | blk.19.post_ffw_norm_2.weight | 0x1bb04cb00 | 0x2c00 | +| 439 | blk.19.pre_ffw_norm_2.weight | 0x1bb04f700 | 0x2c00 | +| 440 | blk.20.attn_k.weight | 0x1bb052300 | 0x21b000 | +| 441 | blk.20.attn_k_norm.weight | 0x1bb26d300 | 0x400 | +| 442 | blk.20.attn_norm.weight | 0x1bb26d700 | 0x2c00 | +| 443 | blk.20.attn_output.weight | 0x1bb270300 | 0x5d8000 | +| 444 | blk.20.attn_q.weight | 0x1bb848300 | 0x436000 | +| 445 | blk.20.attn_q_norm.weight | 0x1bbc7e300 | 0x400 | +| 446 | blk.20.attn_v.weight | 0x1bbc7e700 | 0x2ec000 | +| 447 | blk.20.ffn_down.weight | 0x1bbf6a700 | 0x330c00 | +| 448 | blk.20.ffn_down_exps.scale | 0x1bc29b300 | 0x200 | +| 449 | blk.20.ffn_down_exps.weight | 0x1bc29b500 | 0x8820000 | +| 450 | blk.20.ffn_gate.weight | 0x1c4abb500 | 0x22bd80 | +| 451 | blk.20.ffn_gate_inp.scale | 0x1c4ce7280 | 0x2c00 | +| 452 | blk.20.ffn_gate_inp.weight | 0x1c4ce9e80 | 0x160000 | +| 453 | blk.20.ffn_gate_up_exps.weight | 0x1c4e49e80 | 0xb948000 | +| 454 | blk.20.ffn_norm.weight | 0x1d0791e80 | 0x2c00 | +| 455 | blk.20.ffn_up.weight | 0x1d0794a80 | 0x22bd80 | +| 456 | blk.20.layer_output_scale.weight | 0x1d09c0800 | 0x4 | +| 457 | blk.20.post_attention_norm.weight | 0x1d09c0820 | 0x2c00 | +| 458 | blk.20.post_ffw_norm.weight | 0x1d09c3420 | 0x2c00 | +| 459 | blk.20.post_ffw_norm_1.weight | 0x1d09c6020 | 0x2c00 | +| 460 | blk.20.post_ffw_norm_2.weight | 0x1d09c8c20 | 0x2c00 | +| 461 | blk.20.pre_ffw_norm_2.weight | 0x1d09cb820 | 0x2c00 | +| 462 | blk.21.attn_k.weight | 0x1d09ce420 | 0x21b000 | +| 463 | blk.21.attn_k_norm.weight | 0x1d0be9420 | 0x400 | +| 464 | blk.21.attn_norm.weight | 0x1d0be9820 | 0x2c00 | +| 465 | blk.21.attn_output.weight | 0x1d0bec420 | 0x5d8000 | +| 466 | blk.21.attn_q.weight | 0x1d11c4420 | 0x436000 | +| 467 | blk.21.attn_q_norm.weight | 0x1d15fa420 | 0x400 | +| 468 | blk.21.attn_v.weight | 0x1d15fa820 | 0x2ec000 | +| 469 | blk.21.ffn_down.weight | 0x1d18e6820 | 0x330c00 | +| 470 | blk.21.ffn_down_exps.scale | 0x1d1c17420 | 0x200 | +| 471 | blk.21.ffn_down_exps.weight | 0x1d1c17620 | 0x8820000 | +| 472 | blk.21.ffn_gate.weight | 0x1da437620 | 0x22bd80 | +| 473 | blk.21.ffn_gate_inp.scale | 0x1da6633a0 | 0x2c00 | +| 474 | blk.21.ffn_gate_inp.weight | 0x1da665fa0 | 0x160000 | +| 475 | blk.21.ffn_gate_up_exps.weight | 0x1da7c5fa0 | 0xb948000 | +| 476 | blk.21.ffn_norm.weight | 0x1e610dfa0 | 0x2c00 | +| 477 | blk.21.ffn_up.weight | 0x1e6110ba0 | 0x22bd80 | +| 478 | blk.21.layer_output_scale.weight | 0x1e633c920 | 0x4 | +| 479 | blk.21.post_attention_norm.weight | 0x1e633c940 | 0x2c00 | +| 480 | blk.21.post_ffw_norm.weight | 0x1e633f540 | 0x2c00 | +| 481 | blk.21.post_ffw_norm_1.weight | 0x1e6342140 | 0x2c00 | +| 482 | blk.21.post_ffw_norm_2.weight | 0x1e6344d40 | 0x2c00 | +| 483 | blk.21.pre_ffw_norm_2.weight | 0x1e6347940 | 0x2c00 | +| 484 | blk.22.attn_k.weight | 0x1e634a540 | 0x21b000 | +| 485 | blk.22.attn_k_norm.weight | 0x1e6565540 | 0x400 | +| 486 | blk.22.attn_norm.weight | 0x1e6565940 | 0x2c00 | +| 487 | blk.22.attn_output.weight | 0x1e6568540 | 0x5d8000 | +| 488 | blk.22.attn_q.weight | 0x1e6b40540 | 0x436000 | +| 489 | blk.22.attn_q_norm.weight | 0x1e6f76540 | 0x400 | +| 490 | blk.22.attn_v.weight | 0x1e6f76940 | 0x2ec000 | +| 491 | blk.22.ffn_down.weight | 0x1e7262940 | 0x330c00 | +| 492 | blk.22.ffn_down_exps.scale | 0x1e7593540 | 0x200 | +| 493 | blk.22.ffn_down_exps.weight | 0x1e7593740 | 0x8820000 | +| 494 | blk.22.ffn_gate.weight | 0x1efdb3740 | 0x22bd80 | +| 495 | blk.22.ffn_gate_inp.scale | 0x1effdf4c0 | 0x2c00 | +| 496 | blk.22.ffn_gate_inp.weight | 0x1effe20c0 | 0x160000 | +| 497 | blk.22.ffn_gate_up_exps.weight | 0x1f01420c0 | 0x9ed0000 | +| 498 | blk.22.ffn_norm.weight | 0x1fa0120c0 | 0x2c00 | +| 499 | blk.22.ffn_up.weight | 0x1fa014cc0 | 0x22bd80 | +| 500 | blk.22.layer_output_scale.weight | 0x1fa240a40 | 0x4 | +| 501 | blk.22.post_attention_norm.weight | 0x1fa240a60 | 0x2c00 | +| 502 | blk.22.post_ffw_norm.weight | 0x1fa243660 | 0x2c00 | +| 503 | blk.22.post_ffw_norm_1.weight | 0x1fa246260 | 0x2c00 | +| 504 | blk.22.post_ffw_norm_2.weight | 0x1fa248e60 | 0x2c00 | +| 505 | blk.22.pre_ffw_norm_2.weight | 0x1fa24ba60 | 0x2c00 | +| 506 | blk.23.attn_k.weight | 0x1fa24e660 | 0x176000 | +| 507 | blk.23.attn_k_norm.weight | 0x1fa3c4660 | 0x800 | +| 508 | blk.23.attn_norm.weight | 0x1fa3c4e60 | 0x2c00 | +| 509 | blk.23.attn_output.weight | 0x1fa3c7a60 | 0x86c000 | +| 510 | blk.23.attn_q.weight | 0x1fac33a60 | 0x974000 | +| 511 | blk.23.attn_q_norm.weight | 0x1fb5a7a60 | 0x800 | +| 512 | blk.23.ffn_down.weight | 0x1fb5a8260 | 0x330c00 | +| 513 | blk.23.ffn_down_exps.scale | 0x1fb8d8e60 | 0x200 | +| 514 | blk.23.ffn_down_exps.weight | 0x1fb8d9060 | 0x8820000 | +| 515 | blk.23.ffn_gate.weight | 0x2040f9060 | 0x1dc700 | +| 516 | blk.23.ffn_gate_inp.scale | 0x2042d5760 | 0x2c00 | +| 517 | blk.23.ffn_gate_inp.weight | 0x2042d8360 | 0x160000 | +| 518 | blk.23.ffn_gate_up_exps.weight | 0x204438360 | 0xb948000 | +| 519 | blk.23.ffn_norm.weight | 0x20fd80360 | 0x2c00 | +| 520 | blk.23.ffn_up.weight | 0x20fd82f60 | 0x22bd80 | +| 521 | blk.23.layer_output_scale.weight | 0x20ffaece0 | 0x4 | +| 522 | blk.23.post_attention_norm.weight | 0x20ffaed00 | 0x2c00 | +| 523 | blk.23.post_ffw_norm.weight | 0x20ffb1900 | 0x2c00 | +| 524 | blk.23.post_ffw_norm_1.weight | 0x20ffb4500 | 0x2c00 | +| 525 | blk.23.post_ffw_norm_2.weight | 0x20ffb7100 | 0x2c00 | +| 526 | blk.23.pre_ffw_norm_2.weight | 0x20ffb9d00 | 0x2c00 | +| 527 | blk.24.attn_k.weight | 0x20ffbc900 | 0x21b000 | +| 528 | blk.24.attn_k_norm.weight | 0x2101d7900 | 0x400 | +| 529 | blk.24.attn_norm.weight | 0x2101d7d00 | 0x2c00 | +| 530 | blk.24.attn_output.weight | 0x2101da900 | 0x4ba000 | +| 531 | blk.24.attn_q.weight | 0x210694900 | 0x436000 | +| 532 | blk.24.attn_q_norm.weight | 0x210aca900 | 0x400 | +| 533 | blk.24.attn_v.weight | 0x210acad00 | 0x2ec000 | +| 534 | blk.24.ffn_down.weight | 0x210db6d00 | 0x330c00 | +| 535 | blk.24.ffn_down_exps.scale | 0x2110e7900 | 0x200 | +| 536 | blk.24.ffn_down_exps.weight | 0x2110e7b00 | 0x8820000 | +| 537 | blk.24.ffn_gate.weight | 0x219907b00 | 0x1dc700 | +| 538 | blk.24.ffn_gate_inp.scale | 0x219ae4200 | 0x2c00 | +| 539 | blk.24.ffn_gate_inp.weight | 0x219ae6e00 | 0x160000 | +| 540 | blk.24.ffn_gate_up_exps.weight | 0x219c46e00 | 0xb948000 | +| 541 | blk.24.ffn_norm.weight | 0x22558ee00 | 0x2c00 | +| 542 | blk.24.ffn_up.weight | 0x225591a00 | 0x22bd80 | +| 543 | blk.24.layer_output_scale.weight | 0x2257bd780 | 0x4 | +| 544 | blk.24.post_attention_norm.weight | 0x2257bd7a0 | 0x2c00 | +| 545 | blk.24.post_ffw_norm.weight | 0x2257c03a0 | 0x2c00 | +| 546 | blk.24.post_ffw_norm_1.weight | 0x2257c2fa0 | 0x2c00 | +| 547 | blk.24.post_ffw_norm_2.weight | 0x2257c5ba0 | 0x2c00 | +| 548 | blk.24.pre_ffw_norm_2.weight | 0x2257c87a0 | 0x2c00 | +| 549 | blk.25.attn_k.weight | 0x2257cb3a0 | 0x21b000 | +| 550 | blk.25.attn_k_norm.weight | 0x2259e63a0 | 0x400 | +| 551 | blk.25.attn_norm.weight | 0x2259e67a0 | 0x2c00 | +| 552 | blk.25.attn_output.weight | 0x2259e93a0 | 0x5d8000 | +| 553 | blk.25.attn_q.weight | 0x225fc13a0 | 0x436000 | +| 554 | blk.25.attn_q_norm.weight | 0x2263f73a0 | 0x400 | +| 555 | blk.25.attn_v.weight | 0x2263f77a0 | 0x2ec000 | +| 556 | blk.25.ffn_down.weight | 0x2266e37a0 | 0x330c00 | +| 557 | blk.25.ffn_down_exps.scale | 0x226a143a0 | 0x200 | +| 558 | blk.25.ffn_down_exps.weight | 0x226a145a0 | 0x8820000 | +| 559 | blk.25.ffn_gate.weight | 0x22f2345a0 | 0x1dc700 | +| 560 | blk.25.ffn_gate_inp.scale | 0x22f410ca0 | 0x2c00 | +| 561 | blk.25.ffn_gate_inp.weight | 0x22f4138a0 | 0x160000 | +| 562 | blk.25.ffn_gate_up_exps.weight | 0x22f5738a0 | 0xb948000 | +| 563 | blk.25.ffn_norm.weight | 0x23aebb8a0 | 0x2c00 | +| 564 | blk.25.ffn_up.weight | 0x23aebe4a0 | 0x1dc700 | +| 565 | blk.25.layer_output_scale.weight | 0x23b09aba0 | 0x4 | +| 566 | blk.25.post_attention_norm.weight | 0x23b09abc0 | 0x2c00 | +| 567 | blk.25.post_ffw_norm.weight | 0x23b09d7c0 | 0x2c00 | +| 568 | blk.25.post_ffw_norm_1.weight | 0x23b0a03c0 | 0x2c00 | +| 569 | blk.25.post_ffw_norm_2.weight | 0x23b0a2fc0 | 0x2c00 | +| 570 | blk.25.pre_ffw_norm_2.weight | 0x23b0a5bc0 | 0x2c00 | +| 571 | blk.26.attn_k.weight | 0x23b0a87c0 | 0x21b000 | +| 572 | blk.26.attn_k_norm.weight | 0x23b2c37c0 | 0x400 | +| 573 | blk.26.attn_norm.weight | 0x23b2c3bc0 | 0x2c00 | +| 574 | blk.26.attn_output.weight | 0x23b2c67c0 | 0x5d8000 | +| 575 | blk.26.attn_q.weight | 0x23b89e7c0 | 0x436000 | +| 576 | blk.26.attn_q_norm.weight | 0x23bcd47c0 | 0x400 | +| 577 | blk.26.attn_v.weight | 0x23bcd4bc0 | 0x2ec000 | +| 578 | blk.26.ffn_down.weight | 0x23bfc0bc0 | 0x330c00 | +| 579 | blk.26.ffn_down_exps.scale | 0x23c2f17c0 | 0x200 | +| 580 | blk.26.ffn_down_exps.weight | 0x23c2f19c0 | 0x8820000 | +| 581 | blk.26.ffn_gate.weight | 0x244b119c0 | 0x1dc700 | +| 582 | blk.26.ffn_gate_inp.scale | 0x244cee0c0 | 0x2c00 | +| 583 | blk.26.ffn_gate_inp.weight | 0x244cf0cc0 | 0x160000 | +| 584 | blk.26.ffn_gate_up_exps.weight | 0x244e50cc0 | 0xb948000 | +| 585 | blk.26.ffn_norm.weight | 0x250798cc0 | 0x2c00 | +| 586 | blk.26.ffn_up.weight | 0x25079b8c0 | 0x1dc700 | +| 587 | blk.26.layer_output_scale.weight | 0x250977fc0 | 0x4 | +| 588 | blk.26.post_attention_norm.weight | 0x250977fe0 | 0x2c00 | +| 589 | blk.26.post_ffw_norm.weight | 0x25097abe0 | 0x2c00 | +| 590 | blk.26.post_ffw_norm_1.weight | 0x25097d7e0 | 0x2c00 | +| 591 | blk.26.post_ffw_norm_2.weight | 0x2509803e0 | 0x2c00 | +| 592 | blk.26.pre_ffw_norm_2.weight | 0x250982fe0 | 0x2c00 | +| 593 | blk.27.attn_k.weight | 0x250985be0 | 0x21b000 | +| 594 | blk.27.attn_k_norm.weight | 0x250ba0be0 | 0x400 | +| 595 | blk.27.attn_norm.weight | 0x250ba0fe0 | 0x2c00 | +| 596 | blk.27.attn_output.weight | 0x250ba3be0 | 0x5d8000 | +| 597 | blk.27.attn_q.weight | 0x25117bbe0 | 0x436000 | +| 598 | blk.27.attn_q_norm.weight | 0x2515b1be0 | 0x400 | +| 599 | blk.27.attn_v.weight | 0x2515b1fe0 | 0x2ec000 | +| 600 | blk.27.ffn_down.weight | 0x25189dfe0 | 0x330c00 | +| 601 | blk.27.ffn_down_exps.scale | 0x251bcebe0 | 0x200 | +| 602 | blk.27.ffn_down_exps.weight | 0x251bcede0 | 0x8820000 | +| 603 | blk.27.ffn_gate.weight | 0x25a3eede0 | 0x1dc700 | +| 604 | blk.27.ffn_gate_inp.scale | 0x25a5cb4e0 | 0x2c00 | +| 605 | blk.27.ffn_gate_inp.weight | 0x25a5ce0e0 | 0x160000 | +| 606 | blk.27.ffn_gate_up_exps.weight | 0x25a72e0e0 | 0xb948000 | +| 607 | blk.27.ffn_norm.weight | 0x2660760e0 | 0x2c00 | +| 608 | blk.27.ffn_up.weight | 0x266078ce0 | 0x1dc700 | +| 609 | blk.27.layer_output_scale.weight | 0x2662553e0 | 0x4 | +| 610 | blk.27.post_attention_norm.weight | 0x266255400 | 0x2c00 | +| 611 | blk.27.post_ffw_norm.weight | 0x266258000 | 0x2c00 | +| 612 | blk.27.post_ffw_norm_1.weight | 0x26625ac00 | 0x2c00 | +| 613 | blk.27.post_ffw_norm_2.weight | 0x26625d800 | 0x2c00 | +| 614 | blk.27.pre_ffw_norm_2.weight | 0x266260400 | 0x2c00 | +| 615 | blk.28.attn_k.weight | 0x266263000 | 0x21b000 | +| 616 | blk.28.attn_k_norm.weight | 0x26647e000 | 0x400 | +| 617 | blk.28.attn_norm.weight | 0x26647e400 | 0x2c00 | +| 618 | blk.28.attn_output.weight | 0x266481000 | 0x630000 | +| 619 | blk.28.attn_q.weight | 0x266ab1000 | 0x436000 | +| 620 | blk.28.attn_q_norm.weight | 0x266ee7000 | 0x400 | +| 621 | blk.28.attn_v.weight | 0x266ee7400 | 0x318000 | +| 622 | blk.28.ffn_down.weight | 0x2671ff400 | 0x330c00 | +| 623 | blk.28.ffn_down_exps.scale | 0x267530000 | 0x200 | +| 624 | blk.28.ffn_down_exps.weight | 0x267530200 | 0x8820000 | +| 625 | blk.28.ffn_gate.weight | 0x26fd50200 | 0x1dc700 | +| 626 | blk.28.ffn_gate_inp.scale | 0x26ff2c900 | 0x2c00 | +| 627 | blk.28.ffn_gate_inp.weight | 0x26ff2f500 | 0x160000 | +| 628 | blk.28.ffn_gate_up_exps.weight | 0x27008f500 | 0xb948000 | +| 629 | blk.28.ffn_norm.weight | 0x27b9d7500 | 0x2c00 | +| 630 | blk.28.ffn_up.weight | 0x27b9da100 | 0x1dc700 | +| 631 | blk.28.layer_output_scale.weight | 0x27bbb6800 | 0x4 | +| 632 | blk.28.post_attention_norm.weight | 0x27bbb6820 | 0x2c00 | +| 633 | blk.28.post_ffw_norm.weight | 0x27bbb9420 | 0x2c00 | +| 634 | blk.28.post_ffw_norm_1.weight | 0x27bbbc020 | 0x2c00 | +| 635 | blk.28.post_ffw_norm_2.weight | 0x27bbbec20 | 0x2c00 | +| 636 | blk.28.pre_ffw_norm_2.weight | 0x27bbc1820 | 0x2c00 | +| 637 | blk.29.attn_k.weight | 0x27bbc4420 | 0x176000 | +| 638 | blk.29.attn_k_norm.weight | 0x27bd3a420 | 0x800 | +| 639 | blk.29.attn_norm.weight | 0x27bd3ac20 | 0x2c00 | +| 640 | blk.29.attn_output.weight | 0x27bd3d820 | 0x86c000 | +| 641 | blk.29.attn_q.weight | 0x27c5a9820 | 0x86c000 | +| 642 | blk.29.attn_q_norm.weight | 0x27ce15820 | 0x800 | +| 643 | blk.29.ffn_down.weight | 0x27ce16020 | 0x330c00 | +| 644 | blk.29.ffn_down_exps.scale | 0x27d146c20 | 0x200 | +| 645 | blk.29.ffn_down_exps.weight | 0x27d146e20 | 0x8820000 | +| 646 | blk.29.ffn_gate.weight | 0x285966e20 | 0x22bd80 | +| 647 | blk.29.ffn_gate_inp.scale | 0x285b92ba0 | 0x2c00 | +| 648 | blk.29.ffn_gate_inp.weight | 0x285b957a0 | 0x160000 | +| 649 | blk.29.ffn_gate_up_exps.weight | 0x285cf57a0 | 0xcff8000 | +| 650 | blk.29.ffn_norm.weight | 0x292ced7a0 | 0x2c00 | +| 651 | blk.29.ffn_up.weight | 0x292cf03a0 | 0x22bd80 | +| 652 | blk.29.layer_output_scale.weight | 0x292f1c120 | 0x4 | +| 653 | blk.29.post_attention_norm.weight | 0x292f1c140 | 0x2c00 | +| 654 | blk.29.post_ffw_norm.weight | 0x292f1ed40 | 0x2c00 | +| 655 | blk.29.post_ffw_norm_1.weight | 0x292f21940 | 0x2c00 | +| 656 | blk.29.post_ffw_norm_2.weight | 0x292f24540 | 0x2c00 | +| 657 | blk.29.pre_ffw_norm_2.weight | 0x292f27140 | 0x2c00 | + +### Base Tensor Group : ~738M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :----------------- | :------------------------------- | :---------------- | :-------------------- | :--- | ------: | +| 0 | output_norm.weight | Output Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 1 | rope_freqs.weight | Rope_Freqs (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 2 | token_embd.weight | Token Embedding (W) | (~738M) 738197504 | 2816 x 262144 x 1 x 1 | Q3_K | 3.4375 | + +- Total elements in base: (~738M) 738200576 +- Percentage of total elements: 2.93% +- Bits per Weight (BPW) for base: 3.4376 bits + + +### Block 0 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :------------------------------- | :------------------------------------------------------------------------------------------ | :---------------- | :-------------------- | :------ | ------: | +| 3 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 4 | blk.0.attn_k_norm.weight | Block 0 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 5 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 6 | blk.0.attn_output.weight | Block 0 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ3_XXS | 3.0625 | +| 7 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 8 | blk.0.attn_q_norm.weight | Block 0 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 9 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | Q2_K | 2.6250 | +| 10 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 11 | blk.0.ffn_down_exps.scale | Block 0 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 12 | blk.0.ffn_down_exps.weight | Block 0 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 13 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 14 | blk.0.ffn_gate_inp.scale | Block 0 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 15 | blk.0.ffn_gate_inp.weight | Block 0 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 16 | blk.0.ffn_gate_up_exps.weight | Block 0 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | Q2_K | 2.6250 | +| 17 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 18 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 19 | blk.0.layer_output_scale.weight | Block 0 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 20 | blk.0.post_attention_norm.weight | Block 0 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 21 | blk.0.post_ffw_norm.weight | Block 0 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 22 | blk.0.post_ffw_norm_1.weight | Block 0 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 23 | blk.0.post_ffw_norm_2.weight | Block 0 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 24 | blk.0.pre_ffw_norm_2.weight | Block 0 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.0: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.0: 3.2525 bits + + +### Block 1 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :------------------------------- | :------------------------------------------------------------------------------------------ | :---------------- | :-------------------- | :------ | ------: | +| 25 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 26 | blk.1.attn_k_norm.weight | Block 1 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 27 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 28 | blk.1.attn_output.weight | Block 1 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 29 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 30 | blk.1.attn_q_norm.weight | Block 1 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 31 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 32 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 33 | blk.1.ffn_down_exps.scale | Block 1 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 34 | blk.1.ffn_down_exps.weight | Block 1 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 35 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 36 | blk.1.ffn_gate_inp.scale | Block 1 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 37 | blk.1.ffn_gate_inp.weight | Block 1 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 38 | blk.1.ffn_gate_up_exps.weight | Block 1 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 39 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 40 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 41 | blk.1.layer_output_scale.weight | Block 1 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 42 | blk.1.post_attention_norm.weight | Block 1 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 43 | blk.1.post_ffw_norm.weight | Block 1 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 44 | blk.1.post_ffw_norm_1.weight | Block 1 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 45 | blk.1.post_ffw_norm_2.weight | Block 1 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 46 | blk.1.pre_ffw_norm_2.weight | Block 1 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.1: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.1: 3.5451 bits + + +### Block 2 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :------------------------------- | :------------------------------------------------------------------------------------------ | :---------------- | :-------------------- | :------ | ------: | +| 47 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 48 | blk.2.attn_k_norm.weight | Block 2 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 49 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 50 | blk.2.attn_output.weight | Block 2 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 51 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 52 | blk.2.attn_q_norm.weight | Block 2 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 53 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 54 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 55 | blk.2.ffn_down_exps.scale | Block 2 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 56 | blk.2.ffn_down_exps.weight | Block 2 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 57 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 58 | blk.2.ffn_gate_inp.scale | Block 2 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 59 | blk.2.ffn_gate_inp.weight | Block 2 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 60 | blk.2.ffn_gate_up_exps.weight | Block 2 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 61 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 62 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 63 | blk.2.layer_output_scale.weight | Block 2 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 64 | blk.2.post_attention_norm.weight | Block 2 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 65 | blk.2.post_ffw_norm.weight | Block 2 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 66 | blk.2.post_ffw_norm_1.weight | Block 2 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 67 | blk.2.post_ffw_norm_2.weight | Block 2 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 68 | blk.2.pre_ffw_norm_2.weight | Block 2 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.2: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.2: 3.5536 bits + + +### Block 3 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :------------------------------- | :------------------------------------------------------------------------------------------ | :---------------- | :-------------------- | :------ | ------: | +| 69 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 70 | blk.3.attn_k_norm.weight | Block 3 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 71 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 72 | blk.3.attn_output.weight | Block 3 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 73 | blk.3.attn_q.weight | Block 3 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 74 | blk.3.attn_q_norm.weight | Block 3 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 75 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 76 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 77 | blk.3.ffn_down_exps.scale | Block 3 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 78 | blk.3.ffn_down_exps.weight | Block 3 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 79 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 80 | blk.3.ffn_gate_inp.scale | Block 3 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 81 | blk.3.ffn_gate_inp.weight | Block 3 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 82 | blk.3.ffn_gate_up_exps.weight | Block 3 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 83 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 84 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 85 | blk.3.layer_output_scale.weight | Block 3 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 86 | blk.3.post_attention_norm.weight | Block 3 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 87 | blk.3.post_ffw_norm.weight | Block 3 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 88 | blk.3.post_ffw_norm_1.weight | Block 3 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 89 | blk.3.post_ffw_norm_2.weight | Block 3 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 90 | blk.3.pre_ffw_norm_2.weight | Block 3 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.3: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.3: 3.5483 bits + + +### Block 4 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :------------------------------- | :------------------------------------------------------------------------------------------ | :---------------- | :-------------------- | :------ | ------: | +| 91 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 92 | blk.4.attn_k_norm.weight | Block 4 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 93 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 94 | blk.4.attn_output.weight | Block 4 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 95 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 96 | blk.4.attn_q_norm.weight | Block 4 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 97 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 98 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 99 | blk.4.ffn_down_exps.scale | Block 4 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 100 | blk.4.ffn_down_exps.weight | Block 4 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 101 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 102 | blk.4.ffn_gate_inp.scale | Block 4 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 103 | blk.4.ffn_gate_inp.weight | Block 4 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 104 | blk.4.ffn_gate_up_exps.weight | Block 4 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | Q2_K | 2.6250 | +| 105 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 106 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 107 | blk.4.layer_output_scale.weight | Block 4 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 108 | blk.4.post_attention_norm.weight | Block 4 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 109 | blk.4.post_ffw_norm.weight | Block 4 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 110 | blk.4.post_ffw_norm_1.weight | Block 4 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 111 | blk.4.post_ffw_norm_2.weight | Block 4 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 112 | blk.4.pre_ffw_norm_2.weight | Block 4 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.4: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.4: 3.2808 bits + + +### Block 5 Tensor Group : ~829M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :------------------------------- | :------------------------------------------------------------------------------------------ | :---------------- | :-------------------- | :------ | ------: | +| 113 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~3M) 2883584 | 2816 x 1024 x 1 x 1 | IQ3_XXS | 3.0625 | +| 114 | blk.5.attn_k_norm.weight | Block 5 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 | +| 115 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 116 | blk.5.attn_output.weight | Block 5 Attention Output (W) | ( ~23M) 23068672 | 8192 x 2816 x 1 x 1 | IQ3_XXS | 3.0625 | +| 117 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~23M) 23068672 | 2816 x 8192 x 1 x 1 | IQ3_XXS | 3.0625 | +| 118 | blk.5.attn_q_norm.weight | Block 5 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 | +| 119 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 120 | blk.5.ffn_down_exps.scale | Block 5 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 121 | blk.5.ffn_down_exps.weight | Block 5 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 122 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 123 | blk.5.ffn_gate_inp.scale | Block 5 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 124 | blk.5.ffn_gate_inp.weight | Block 5 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 125 | blk.5.ffn_gate_up_exps.weight | Block 5 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | Q2_K | 2.6250 | +| 126 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 127 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 128 | blk.5.layer_output_scale.weight | Block 5 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 129 | blk.5.post_attention_norm.weight | Block 5 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 130 | blk.5.post_ffw_norm.weight | Block 5 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 131 | blk.5.post_ffw_norm_1.weight | Block 5 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 132 | blk.5.post_ffw_norm_2.weight | Block 5 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 133 | blk.5.pre_ffw_norm_2.weight | Block 5 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.5: (~829M) 828513409 +- Percentage of total elements: 3.28% +- Bits per Weight (BPW) for blk.5: 3.2554 bits + + +### Block 6 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :------------------------------- | :------------------------------------------------------------------------------------------ | :---------------- | :-------------------- | :------ | ------: | +| 134 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 135 | blk.6.attn_k_norm.weight | Block 6 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 136 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 137 | blk.6.attn_output.weight | Block 6 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ3_S | 3.4375 | +| 138 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 139 | blk.6.attn_q_norm.weight | Block 6 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 140 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 141 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 142 | blk.6.ffn_down_exps.scale | Block 6 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 143 | blk.6.ffn_down_exps.weight | Block 6 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 144 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 145 | blk.6.ffn_gate_inp.scale | Block 6 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 146 | blk.6.ffn_gate_inp.weight | Block 6 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 147 | blk.6.ffn_gate_up_exps.weight | Block 6 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | Q2_K | 2.6250 | +| 148 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 149 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 150 | blk.6.layer_output_scale.weight | Block 6 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 151 | blk.6.post_attention_norm.weight | Block 6 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 152 | blk.6.post_ffw_norm.weight | Block 6 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 153 | blk.6.post_ffw_norm_1.weight | Block 6 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 154 | blk.6.post_ffw_norm_2.weight | Block 6 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 155 | blk.6.pre_ffw_norm_2.weight | Block 6 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.6: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.6: 3.2609 bits + + +### Block 7 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :------------------------------- | :------------------------------------------------------------------------------------------ | :---------------- | :-------------------- | :------ | ------: | +| 156 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 157 | blk.7.attn_k_norm.weight | Block 7 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 158 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 159 | blk.7.attn_output.weight | Block 7 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 160 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 161 | blk.7.attn_q_norm.weight | Block 7 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 162 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 163 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 164 | blk.7.ffn_down_exps.scale | Block 7 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 165 | blk.7.ffn_down_exps.weight | Block 7 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 166 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 167 | blk.7.ffn_gate_inp.scale | Block 7 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 168 | blk.7.ffn_gate_inp.weight | Block 7 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 169 | blk.7.ffn_gate_up_exps.weight | Block 7 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 170 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 171 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 172 | blk.7.layer_output_scale.weight | Block 7 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 173 | blk.7.post_attention_norm.weight | Block 7 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 174 | blk.7.post_ffw_norm.weight | Block 7 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 175 | blk.7.post_ffw_norm_1.weight | Block 7 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 176 | blk.7.post_ffw_norm_2.weight | Block 7 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 177 | blk.7.pre_ffw_norm_2.weight | Block 7 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.7: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.7: 3.5451 bits + + +### Block 8 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :------------------------------- | :------------------------------------------------------------------------------------------ | :---------------- | :-------------------- | :------ | ------: | +| 178 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 179 | blk.8.attn_k_norm.weight | Block 8 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 180 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 181 | blk.8.attn_output.weight | Block 8 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 182 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 183 | blk.8.attn_q_norm.weight | Block 8 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 184 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 185 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 186 | blk.8.ffn_down_exps.scale | Block 8 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 187 | blk.8.ffn_down_exps.weight | Block 8 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 188 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 189 | blk.8.ffn_gate_inp.scale | Block 8 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 190 | blk.8.ffn_gate_inp.weight | Block 8 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 191 | blk.8.ffn_gate_up_exps.weight | Block 8 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 192 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 193 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 194 | blk.8.layer_output_scale.weight | Block 8 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 195 | blk.8.post_attention_norm.weight | Block 8 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 196 | blk.8.post_ffw_norm.weight | Block 8 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 197 | blk.8.post_ffw_norm_1.weight | Block 8 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 198 | blk.8.post_ffw_norm_2.weight | Block 8 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 199 | blk.8.pre_ffw_norm_2.weight | Block 8 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.8: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.8: 3.5451 bits + + +### Block 9 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :------------------------------- | :------------------------------------------------------------------------------------------ | :---------------- | :-------------------- | :------ | ------: | +| 200 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 201 | blk.9.attn_k_norm.weight | Block 9 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 202 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 203 | blk.9.attn_output.weight | Block 9 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 204 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 205 | blk.9.attn_q_norm.weight | Block 9 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 206 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 207 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 208 | blk.9.ffn_down_exps.scale | Block 9 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 209 | blk.9.ffn_down_exps.weight | Block 9 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 210 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 211 | blk.9.ffn_gate_inp.scale | Block 9 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 212 | blk.9.ffn_gate_inp.weight | Block 9 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 213 | blk.9.ffn_gate_up_exps.weight | Block 9 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 214 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 215 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 216 | blk.9.layer_output_scale.weight | Block 9 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 217 | blk.9.post_attention_norm.weight | Block 9 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 218 | blk.9.post_ffw_norm.weight | Block 9 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 219 | blk.9.post_ffw_norm_1.weight | Block 9 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 220 | blk.9.post_ffw_norm_2.weight | Block 9 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 221 | blk.9.pre_ffw_norm_2.weight | Block 9 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.9: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.9: 3.5599 bits + + +### Block 10 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 222 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 223 | blk.10.attn_k_norm.weight | Block 10 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 224 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 225 | blk.10.attn_output.weight | Block 10 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 226 | blk.10.attn_q.weight | Block 10 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 227 | blk.10.attn_q_norm.weight | Block 10 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 228 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 229 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 230 | blk.10.ffn_down_exps.scale | Block 10 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 231 | blk.10.ffn_down_exps.weight | Block 10 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 232 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 233 | blk.10.ffn_gate_inp.scale | Block 10 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 234 | blk.10.ffn_gate_inp.weight | Block 10 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 235 | blk.10.ffn_gate_up_exps.weight | Block 10 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | Q2_K | 2.6250 | +| 236 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 237 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 238 | blk.10.layer_output_scale.weight | Block 10 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 239 | blk.10.post_attention_norm.weight | Block 10 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 240 | blk.10.post_ffw_norm.weight | Block 10 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 241 | blk.10.post_ffw_norm_1.weight | Block 10 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 242 | blk.10.post_ffw_norm_2.weight | Block 10 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 243 | blk.10.pre_ffw_norm_2.weight | Block 10 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.10: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.10: 3.2872 bits + + +### Block 11 Tensor Group : ~829M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 244 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~3M) 2883584 | 2816 x 1024 x 1 x 1 | IQ3_XXS | 3.0625 | +| 245 | blk.11.attn_k_norm.weight | Block 11 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 | +| 246 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 247 | blk.11.attn_output.weight | Block 11 Attention Output (W) | ( ~23M) 23068672 | 8192 x 2816 x 1 x 1 | IQ3_XXS | 3.0625 | +| 248 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~23M) 23068672 | 2816 x 8192 x 1 x 1 | IQ3_XXS | 3.0625 | +| 249 | blk.11.attn_q_norm.weight | Block 11 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 | +| 250 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 251 | blk.11.ffn_down_exps.scale | Block 11 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 252 | blk.11.ffn_down_exps.weight | Block 11 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 253 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 254 | blk.11.ffn_gate_inp.scale | Block 11 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 255 | blk.11.ffn_gate_inp.weight | Block 11 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 256 | blk.11.ffn_gate_up_exps.weight | Block 11 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 257 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 258 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 259 | blk.11.layer_output_scale.weight | Block 11 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 260 | blk.11.post_attention_norm.weight | Block 11 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 261 | blk.11.post_ffw_norm.weight | Block 11 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 262 | blk.11.post_ffw_norm_1.weight | Block 11 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 263 | blk.11.post_ffw_norm_2.weight | Block 11 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 264 | blk.11.pre_ffw_norm_2.weight | Block 11 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.11: (~829M) 828513409 +- Percentage of total elements: 3.28% +- Bits per Weight (BPW) for blk.11: 3.5265 bits + + +### Block 12 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 265 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 266 | blk.12.attn_k_norm.weight | Block 12 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 267 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 268 | blk.12.attn_output.weight | Block 12 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ3_XXS | 3.0625 | +| 269 | blk.12.attn_q.weight | Block 12 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 270 | blk.12.attn_q_norm.weight | Block 12 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 271 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 272 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 273 | blk.12.ffn_down_exps.scale | Block 12 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 274 | blk.12.ffn_down_exps.weight | Block 12 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 275 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 276 | blk.12.ffn_gate_inp.scale | Block 12 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 277 | blk.12.ffn_gate_inp.weight | Block 12 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 278 | blk.12.ffn_gate_up_exps.weight | Block 12 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 279 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 280 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 281 | blk.12.layer_output_scale.weight | Block 12 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 282 | blk.12.post_attention_norm.weight | Block 12 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 283 | blk.12.post_ffw_norm.weight | Block 12 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 284 | blk.12.post_ffw_norm_1.weight | Block 12 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 285 | blk.12.post_ffw_norm_2.weight | Block 12 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 286 | blk.12.pre_ffw_norm_2.weight | Block 12 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.12: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.12: 3.5347 bits + + +### Block 13 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 287 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 288 | blk.13.attn_k_norm.weight | Block 13 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 289 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 290 | blk.13.attn_output.weight | Block 13 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 291 | blk.13.attn_q.weight | Block 13 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 292 | blk.13.attn_q_norm.weight | Block 13 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 293 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 294 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 295 | blk.13.ffn_down_exps.scale | Block 13 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 296 | blk.13.ffn_down_exps.weight | Block 13 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 297 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 298 | blk.13.ffn_gate_inp.scale | Block 13 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 299 | blk.13.ffn_gate_inp.weight | Block 13 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 300 | blk.13.ffn_gate_up_exps.weight | Block 13 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 301 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 302 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 303 | blk.13.layer_output_scale.weight | Block 13 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 304 | blk.13.post_attention_norm.weight | Block 13 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 305 | blk.13.post_ffw_norm.weight | Block 13 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 306 | blk.13.post_ffw_norm_1.weight | Block 13 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 307 | blk.13.post_ffw_norm_2.weight | Block 13 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 308 | blk.13.pre_ffw_norm_2.weight | Block 13 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.13: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.13: 3.5599 bits + + +### Block 14 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 309 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 310 | blk.14.attn_k_norm.weight | Block 14 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 311 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 312 | blk.14.attn_output.weight | Block 14 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 313 | blk.14.attn_q.weight | Block 14 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 314 | blk.14.attn_q_norm.weight | Block 14 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 315 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 316 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 317 | blk.14.ffn_down_exps.scale | Block 14 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 318 | blk.14.ffn_down_exps.weight | Block 14 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 319 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 320 | blk.14.ffn_gate_inp.scale | Block 14 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 321 | blk.14.ffn_gate_inp.weight | Block 14 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 322 | blk.14.ffn_gate_up_exps.weight | Block 14 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 323 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 324 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 325 | blk.14.layer_output_scale.weight | Block 14 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 326 | blk.14.post_attention_norm.weight | Block 14 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 327 | blk.14.post_ffw_norm.weight | Block 14 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 328 | blk.14.post_ffw_norm_1.weight | Block 14 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 329 | blk.14.post_ffw_norm_2.weight | Block 14 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 330 | blk.14.pre_ffw_norm_2.weight | Block 14 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.14: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.14: 3.5515 bits + + +### Block 15 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 331 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 332 | blk.15.attn_k_norm.weight | Block 15 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 333 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 334 | blk.15.attn_output.weight | Block 15 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 335 | blk.15.attn_q.weight | Block 15 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 336 | blk.15.attn_q_norm.weight | Block 15 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 337 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 338 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 339 | blk.15.ffn_down_exps.scale | Block 15 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 340 | blk.15.ffn_down_exps.weight | Block 15 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 341 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 342 | blk.15.ffn_gate_inp.scale | Block 15 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 343 | blk.15.ffn_gate_inp.weight | Block 15 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 344 | blk.15.ffn_gate_up_exps.weight | Block 15 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 345 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 346 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 347 | blk.15.layer_output_scale.weight | Block 15 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 348 | blk.15.post_attention_norm.weight | Block 15 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 349 | blk.15.post_ffw_norm.weight | Block 15 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 350 | blk.15.post_ffw_norm_1.weight | Block 15 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 351 | blk.15.post_ffw_norm_2.weight | Block 15 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 352 | blk.15.pre_ffw_norm_2.weight | Block 15 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.15: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.15: 3.5599 bits + + +### Block 16 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 353 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 354 | blk.16.attn_k_norm.weight | Block 16 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 355 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 356 | blk.16.attn_output.weight | Block 16 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 357 | blk.16.attn_q.weight | Block 16 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 358 | blk.16.attn_q_norm.weight | Block 16 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 359 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 360 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 361 | blk.16.ffn_down_exps.scale | Block 16 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 362 | blk.16.ffn_down_exps.weight | Block 16 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 363 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 364 | blk.16.ffn_gate_inp.scale | Block 16 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 365 | blk.16.ffn_gate_inp.weight | Block 16 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 366 | blk.16.ffn_gate_up_exps.weight | Block 16 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 367 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 368 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 369 | blk.16.layer_output_scale.weight | Block 16 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 370 | blk.16.post_attention_norm.weight | Block 16 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 371 | blk.16.post_ffw_norm.weight | Block 16 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 372 | blk.16.post_ffw_norm_1.weight | Block 16 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 373 | blk.16.post_ffw_norm_2.weight | Block 16 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 374 | blk.16.pre_ffw_norm_2.weight | Block 16 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.16: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.16: 3.5599 bits + + +### Block 17 Tensor Group : ~829M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 375 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~3M) 2883584 | 2816 x 1024 x 1 x 1 | IQ3_S | 3.4375 | +| 376 | blk.17.attn_k_norm.weight | Block 17 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 | +| 377 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 378 | blk.17.attn_output.weight | Block 17 Attention Output (W) | ( ~23M) 23068672 | 8192 x 2816 x 1 x 1 | IQ3_XXS | 3.0625 | +| 379 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~23M) 23068672 | 2816 x 8192 x 1 x 1 | IQ3_S | 3.4375 | +| 380 | blk.17.attn_q_norm.weight | Block 17 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 | +| 381 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 382 | blk.17.ffn_down_exps.scale | Block 17 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 383 | blk.17.ffn_down_exps.weight | Block 17 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 384 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 385 | blk.17.ffn_gate_inp.scale | Block 17 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 386 | blk.17.ffn_gate_inp.weight | Block 17 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 387 | blk.17.ffn_gate_up_exps.weight | Block 17 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 388 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 389 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 390 | blk.17.layer_output_scale.weight | Block 17 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 391 | blk.17.post_attention_norm.weight | Block 17 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 392 | blk.17.post_ffw_norm.weight | Block 17 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 393 | blk.17.post_ffw_norm_1.weight | Block 17 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 394 | blk.17.post_ffw_norm_2.weight | Block 17 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 395 | blk.17.pre_ffw_norm_2.weight | Block 17 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.17: (~829M) 828513409 +- Percentage of total elements: 3.28% +- Bits per Weight (BPW) for blk.17: 3.5383 bits + + +### Block 18 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 396 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 397 | blk.18.attn_k_norm.weight | Block 18 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 398 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 399 | blk.18.attn_output.weight | Block 18 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ3_S | 3.4375 | +| 400 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_S | 3.4375 | +| 401 | blk.18.attn_q_norm.weight | Block 18 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 402 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 403 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 404 | blk.18.ffn_down_exps.scale | Block 18 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 405 | blk.18.ffn_down_exps.weight | Block 18 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 406 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 407 | blk.18.ffn_gate_inp.scale | Block 18 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 408 | blk.18.ffn_gate_inp.weight | Block 18 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 409 | blk.18.ffn_gate_up_exps.weight | Block 18 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 410 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 411 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ4_XS | 4.2500 | +| 412 | blk.18.layer_output_scale.weight | Block 18 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 413 | blk.18.post_attention_norm.weight | Block 18 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 414 | blk.18.post_ffw_norm.weight | Block 18 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 415 | blk.18.post_ffw_norm_1.weight | Block 18 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 416 | blk.18.post_ffw_norm_2.weight | Block 18 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 417 | blk.18.pre_ffw_norm_2.weight | Block 18 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.18: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.18: 3.5540 bits + + +### Block 19 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 418 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 419 | blk.19.attn_k_norm.weight | Block 19 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 420 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 421 | blk.19.attn_output.weight | Block 19 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 422 | blk.19.attn_q.weight | Block 19 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_S | 3.4375 | +| 423 | blk.19.attn_q_norm.weight | Block 19 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 424 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 425 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 426 | blk.19.ffn_down_exps.scale | Block 19 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 427 | blk.19.ffn_down_exps.weight | Block 19 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 428 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 429 | blk.19.ffn_gate_inp.scale | Block 19 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 430 | blk.19.ffn_gate_inp.weight | Block 19 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 431 | blk.19.ffn_gate_up_exps.weight | Block 19 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 432 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 433 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 434 | blk.19.layer_output_scale.weight | Block 19 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 435 | blk.19.post_attention_norm.weight | Block 19 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 436 | blk.19.post_ffw_norm.weight | Block 19 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 437 | blk.19.post_ffw_norm_1.weight | Block 19 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 438 | blk.19.post_ffw_norm_2.weight | Block 19 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 439 | blk.19.pre_ffw_norm_2.weight | Block 19 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.19: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.19: 3.5653 bits + + +### Block 20 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 440 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 441 | blk.20.attn_k_norm.weight | Block 20 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 442 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 443 | blk.20.attn_output.weight | Block 20 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 444 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 445 | blk.20.attn_q_norm.weight | Block 20 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 446 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 447 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 448 | blk.20.ffn_down_exps.scale | Block 20 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 449 | blk.20.ffn_down_exps.weight | Block 20 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 450 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 451 | blk.20.ffn_gate_inp.scale | Block 20 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 452 | blk.20.ffn_gate_inp.weight | Block 20 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 453 | blk.20.ffn_gate_up_exps.weight | Block 20 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 454 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 455 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 456 | blk.20.layer_output_scale.weight | Block 20 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 457 | blk.20.post_attention_norm.weight | Block 20 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 458 | blk.20.post_ffw_norm.weight | Block 20 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 459 | blk.20.post_ffw_norm_1.weight | Block 20 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 460 | blk.20.post_ffw_norm_2.weight | Block 20 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 461 | blk.20.pre_ffw_norm_2.weight | Block 20 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.20: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.20: 3.5599 bits + + +### Block 21 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 462 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 463 | blk.21.attn_k_norm.weight | Block 21 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 464 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 465 | blk.21.attn_output.weight | Block 21 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 466 | blk.21.attn_q.weight | Block 21 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 467 | blk.21.attn_q_norm.weight | Block 21 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 468 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 469 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 470 | blk.21.ffn_down_exps.scale | Block 21 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 471 | blk.21.ffn_down_exps.weight | Block 21 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 472 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 473 | blk.21.ffn_gate_inp.scale | Block 21 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 474 | blk.21.ffn_gate_inp.weight | Block 21 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 475 | blk.21.ffn_gate_up_exps.weight | Block 21 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 476 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 477 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 478 | blk.21.layer_output_scale.weight | Block 21 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 479 | blk.21.post_attention_norm.weight | Block 21 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 480 | blk.21.post_ffw_norm.weight | Block 21 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 481 | blk.21.post_ffw_norm_1.weight | Block 21 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 482 | blk.21.post_ffw_norm_2.weight | Block 21 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 483 | blk.21.pre_ffw_norm_2.weight | Block 21 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.21: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.21: 3.5599 bits + + +### Block 22 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 484 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 485 | blk.22.attn_k_norm.weight | Block 22 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 486 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 487 | blk.22.attn_output.weight | Block 22 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 488 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 489 | blk.22.attn_q_norm.weight | Block 22 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 490 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 491 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 492 | blk.22.ffn_down_exps.scale | Block 22 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 493 | blk.22.ffn_down_exps.weight | Block 22 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 494 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 495 | blk.22.ffn_gate_inp.scale | Block 22 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 496 | blk.22.ffn_gate_inp.weight | Block 22 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 497 | blk.22.ffn_gate_up_exps.weight | Block 22 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | Q2_K | 2.6250 | +| 498 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 499 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 500 | blk.22.layer_output_scale.weight | Block 22 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 501 | blk.22.post_attention_norm.weight | Block 22 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 502 | blk.22.post_ffw_norm.weight | Block 22 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 503 | blk.22.post_ffw_norm_1.weight | Block 22 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 504 | blk.22.post_ffw_norm_2.weight | Block 22 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 505 | blk.22.pre_ffw_norm_2.weight | Block 22 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.22: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.22: 3.2872 bits + + +### Block 23 Tensor Group : ~829M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 506 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~3M) 2883584 | 2816 x 1024 x 1 x 1 | IQ4_XS | 4.2500 | +| 507 | blk.23.attn_k_norm.weight | Block 23 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 | +| 508 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 509 | blk.23.attn_output.weight | Block 23 Attention Output (W) | ( ~23M) 23068672 | 8192 x 2816 x 1 x 1 | IQ3_XXS | 3.0625 | +| 510 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~23M) 23068672 | 2816 x 8192 x 1 x 1 | IQ3_S | 3.4375 | +| 511 | blk.23.attn_q_norm.weight | Block 23 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 | +| 512 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 513 | blk.23.ffn_down_exps.scale | Block 23 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 514 | blk.23.ffn_down_exps.weight | Block 23 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 515 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 516 | blk.23.ffn_gate_inp.scale | Block 23 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 517 | blk.23.ffn_gate_inp.weight | Block 23 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 518 | blk.23.ffn_gate_up_exps.weight | Block 23 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 519 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 520 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 521 | blk.23.layer_output_scale.weight | Block 23 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 522 | blk.23.post_attention_norm.weight | Block 23 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 523 | blk.23.post_ffw_norm.weight | Block 23 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 524 | blk.23.post_ffw_norm_1.weight | Block 23 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 525 | blk.23.post_ffw_norm_2.weight | Block 23 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 526 | blk.23.pre_ffw_norm_2.weight | Block 23 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.23: (~829M) 828513409 +- Percentage of total elements: 3.28% +- Bits per Weight (BPW) for blk.23: 3.5379 bits + + +### Block 24 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 527 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 528 | blk.24.attn_k_norm.weight | Block 24 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 529 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 530 | blk.24.attn_output.weight | Block 24 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ3_S | 3.4375 | +| 531 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 532 | blk.24.attn_q_norm.weight | Block 24 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 533 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 534 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 535 | blk.24.ffn_down_exps.scale | Block 24 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 536 | blk.24.ffn_down_exps.weight | Block 24 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 537 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 538 | blk.24.ffn_gate_inp.scale | Block 24 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 539 | blk.24.ffn_gate_inp.weight | Block 24 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 540 | blk.24.ffn_gate_up_exps.weight | Block 24 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 541 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 542 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 543 | blk.24.layer_output_scale.weight | Block 24 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 544 | blk.24.post_attention_norm.weight | Block 24 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 545 | blk.24.post_ffw_norm.weight | Block 24 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 546 | blk.24.post_ffw_norm_1.weight | Block 24 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 547 | blk.24.post_ffw_norm_2.weight | Block 24 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 548 | blk.24.pre_ffw_norm_2.weight | Block 24 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.24: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.24: 3.5452 bits + + +### Block 25 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 549 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 550 | blk.25.attn_k_norm.weight | Block 25 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 551 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 552 | blk.25.attn_output.weight | Block 25 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 553 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 554 | blk.25.attn_q_norm.weight | Block 25 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 555 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 556 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 557 | blk.25.ffn_down_exps.scale | Block 25 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 558 | blk.25.ffn_down_exps.weight | Block 25 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 559 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 560 | blk.25.ffn_gate_inp.scale | Block 25 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 561 | blk.25.ffn_gate_inp.weight | Block 25 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 562 | blk.25.ffn_gate_up_exps.weight | Block 25 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 563 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 564 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 565 | blk.25.layer_output_scale.weight | Block 25 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 566 | blk.25.post_attention_norm.weight | Block 25 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 567 | blk.25.post_ffw_norm.weight | Block 25 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 568 | blk.25.post_ffw_norm_1.weight | Block 25 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 569 | blk.25.post_ffw_norm_2.weight | Block 25 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 570 | blk.25.pre_ffw_norm_2.weight | Block 25 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.25: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.25: 3.5536 bits + + +### Block 26 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 571 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 572 | blk.26.attn_k_norm.weight | Block 26 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 573 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 574 | blk.26.attn_output.weight | Block 26 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 575 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 576 | blk.26.attn_q_norm.weight | Block 26 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 577 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 578 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 579 | blk.26.ffn_down_exps.scale | Block 26 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 580 | blk.26.ffn_down_exps.weight | Block 26 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 581 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 582 | blk.26.ffn_gate_inp.scale | Block 26 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 583 | blk.26.ffn_gate_inp.weight | Block 26 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 584 | blk.26.ffn_gate_up_exps.weight | Block 26 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 585 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 586 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 587 | blk.26.layer_output_scale.weight | Block 26 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 588 | blk.26.post_attention_norm.weight | Block 26 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 589 | blk.26.post_ffw_norm.weight | Block 26 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 590 | blk.26.post_ffw_norm_1.weight | Block 26 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 591 | blk.26.post_ffw_norm_2.weight | Block 26 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 592 | blk.26.pre_ffw_norm_2.weight | Block 26 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.26: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.26: 3.5536 bits + + +### Block 27 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 593 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 594 | blk.27.attn_k_norm.weight | Block 27 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 595 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 596 | blk.27.attn_output.weight | Block 27 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | IQ4_XS | 4.2500 | +| 597 | blk.27.attn_q.weight | Block 27 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 598 | blk.27.attn_q_norm.weight | Block 27 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 599 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ4_XS | 4.2500 | +| 600 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 601 | blk.27.ffn_down_exps.scale | Block 27 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 602 | blk.27.ffn_down_exps.weight | Block 27 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 603 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 604 | blk.27.ffn_gate_inp.scale | Block 27 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 605 | blk.27.ffn_gate_inp.weight | Block 27 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 606 | blk.27.ffn_gate_up_exps.weight | Block 27 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 607 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 608 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 609 | blk.27.layer_output_scale.weight | Block 27 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 610 | blk.27.post_attention_norm.weight | Block 27 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 611 | blk.27.post_ffw_norm.weight | Block 27 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 612 | blk.27.post_ffw_norm_1.weight | Block 27 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 613 | blk.27.post_ffw_norm_2.weight | Block 27 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 614 | blk.27.pre_ffw_norm_2.weight | Block 27 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.27: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.27: 3.5536 bits + + +### Block 28 Tensor Group : ~814M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 615 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | IQ3_XXS | 3.0625 | +| 616 | blk.28.attn_k_norm.weight | Block 28 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 617 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 618 | blk.28.attn_output.weight | Block 28 Attention Output (W) | ( ~12M) 11534336 | 4096 x 2816 x 1 x 1 | Q4_K | 4.5000 | +| 619 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ3_XXS | 3.0625 | +| 620 | blk.28.attn_q_norm.weight | Block 28 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 | +| 621 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~6M) 5767168 | 2816 x 2048 x 1 x 1 | Q4_K | 4.5000 | +| 622 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 623 | blk.28.ffn_down_exps.scale | Block 28 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 624 | blk.28.ffn_down_exps.weight | Block 28 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 625 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 626 | blk.28.ffn_gate_inp.scale | Block 28 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 627 | blk.28.ffn_gate_inp.weight | Block 28 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 628 | blk.28.ffn_gate_up_exps.weight | Block 28 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | IQ3_XXS | 3.0625 | +| 629 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 630 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | Q2_K | 2.6250 | +| 631 | blk.28.layer_output_scale.weight | Block 28 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 632 | blk.28.post_attention_norm.weight | Block 28 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 633 | blk.28.post_ffw_norm.weight | Block 28 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 634 | blk.28.post_ffw_norm_1.weight | Block 28 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 635 | blk.28.post_ffw_norm_2.weight | Block 28 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 636 | blk.28.pre_ffw_norm_2.weight | Block 28 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.28: (~814M) 814094977 +- Percentage of total elements: 3.23% +- Bits per Weight (BPW) for blk.28: 3.5589 bits + + +### Block 29 Tensor Group : ~829M Elements + +| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW | +| ---: | :-------------------------------- | :------------------------------------------------------------------------------------------- | :---------------- | :-------------------- | :------ | ------: | +| 637 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~3M) 2883584 | 2816 x 1024 x 1 x 1 | IQ4_XS | 4.2500 | +| 638 | blk.29.attn_k_norm.weight | Block 29 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 | +| 639 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 640 | blk.29.attn_output.weight | Block 29 Attention Output (W) | ( ~23M) 23068672 | 8192 x 2816 x 1 x 1 | IQ3_XXS | 3.0625 | +| 641 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~23M) 23068672 | 2816 x 8192 x 1 x 1 | IQ3_XXS | 3.0625 | +| 642 | blk.29.attn_q_norm.weight | Block 29 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 | +| 643 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | ( ~6M) 5947392 | 2112 x 2816 x 1 x 1 | IQ4_NL | 4.5000 | +| 644 | blk.29.ffn_down_exps.scale | Block 29 Ffn_Down_Exps Scale | ( 128) 128 | 128 x 1 x 1 x 1 | F32 | 32.0000 | +| 645 | blk.29.ffn_down_exps.weight | Block 29 Ffn_Down_Exps (W) | (~254M) 253755392 | 704 x 2816 x 128 x 1 | IQ4_NL | 4.5000 | +| 646 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 647 | blk.29.ffn_gate_inp.scale | Block 29 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models Scale | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 648 | blk.29.ffn_gate_inp.weight | Block 29 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~360K) 360448 | 2816 x 128 x 1 x 1 | F32 | 32.0000 | +| 649 | blk.29.ffn_gate_up_exps.weight | Block 29 Ffn_Gate_Up_Exps (W) | (~508M) 507510784 | 2816 x 1408 x 128 x 1 | Q3_K | 3.4375 | +| 650 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 651 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | ( ~6M) 5947392 | 2816 x 2112 x 1 x 1 | IQ3_XXS | 3.0625 | +| 652 | blk.29.layer_output_scale.weight | Block 29 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 | +| 653 | blk.29.post_attention_norm.weight | Block 29 Post_Attention_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 654 | blk.29.post_ffw_norm.weight | Block 29 Post_Ffw_Norm (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 655 | blk.29.post_ffw_norm_1.weight | Block 29 Post_Ffw_Norm_1 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 656 | blk.29.post_ffw_norm_2.weight | Block 29 Post_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | +| 657 | blk.29.pre_ffw_norm_2.weight | Block 29 Pre_Ffw_Norm_2 (W) | ( ~3K) 2816 | 2816 x 1 x 1 x 1 | F32 | 32.0000 | + +- Total elements in blk.29: (~829M) 828513409 +- Percentage of total elements: 3.28% +- Bits per Weight (BPW) for blk.29: 3.7604 bits + + +Total BPW for gemma-4-26B-A4B-it-Q3_K.gguf: 3.5000 bits