# gemma-4-26B-A4B-it-Q2_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 | 28 | | 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-Q2\_K.gguf - GGUF Internal File Dump](#userseddevelopmentaihfgemma-4-26b-a4b-it-wipgemma-4-26b-a4b-it-q2_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 | 0xe700000 | | 3 | blk.0.attn_k.weight | 0xf619c00 | 0x113000 | | 4 | blk.0.attn_k_norm.weight | 0xf72cc00 | 0x400 | | 5 | blk.0.attn_norm.weight | 0xf72d000 | 0x2c00 | | 6 | blk.0.attn_output.weight | 0xf72fc00 | 0x226000 | | 7 | blk.0.attn_q.weight | 0xf955c00 | 0x226000 | | 8 | blk.0.attn_q_norm.weight | 0xfb7bc00 | 0x400 | | 9 | blk.0.attn_v.weight | 0xfb7c000 | 0x113000 | | 10 | blk.0.ffn_down.weight | 0xfc8f000 | 0x330c00 | | 11 | blk.0.ffn_down_exps.scale | 0xffbfc00 | 0x200 | | 12 | blk.0.ffn_down_exps.weight | 0xffbfe00 | 0x8820000 | | 13 | blk.0.ffn_gate.weight | 0x187dfe00 | 0x11b980 | | 14 | blk.0.ffn_gate_inp.scale | 0x188fb780 | 0x2c00 | | 15 | blk.0.ffn_gate_inp.weight | 0x188fe380 | 0x160000 | | 16 | blk.0.ffn_gate_up_exps.weight | 0x18a5e380 | 0x5e88000 | | 17 | blk.0.ffn_norm.weight | 0x1e8e6380 | 0x2c00 | | 18 | blk.0.ffn_up.weight | 0x1e8e8f80 | 0x11b980 | | 19 | blk.0.layer_output_scale.weight | 0x1ea04900 | 0x4 | | 20 | blk.0.post_attention_norm.weight | 0x1ea04920 | 0x2c00 | | 21 | blk.0.post_ffw_norm.weight | 0x1ea07520 | 0x2c00 | | 22 | blk.0.post_ffw_norm_1.weight | 0x1ea0a120 | 0x2c00 | | 23 | blk.0.post_ffw_norm_2.weight | 0x1ea0cd20 | 0x2c00 | | 24 | blk.0.pre_ffw_norm_2.weight | 0x1ea0f920 | 0x2c00 | | 25 | blk.1.attn_k.weight | 0x1ea12520 | 0x113000 | | 26 | blk.1.attn_k_norm.weight | 0x1eb25520 | 0x400 | | 27 | blk.1.attn_norm.weight | 0x1eb25920 | 0x2c00 | | 28 | blk.1.attn_output.weight | 0x1eb28520 | 0x226000 | | 29 | blk.1.attn_q.weight | 0x1ed4e520 | 0x226000 | | 30 | blk.1.attn_q_norm.weight | 0x1ef74520 | 0x400 | | 31 | blk.1.attn_v.weight | 0x1ef74920 | 0x113000 | | 32 | blk.1.ffn_down.weight | 0x1f087920 | 0x330c00 | | 33 | blk.1.ffn_down_exps.scale | 0x1f3b8520 | 0x200 | | 34 | blk.1.ffn_down_exps.weight | 0x1f3b8720 | 0x8820000 | | 35 | blk.1.ffn_gate.weight | 0x27bd8720 | 0x11b980 | | 36 | blk.1.ffn_gate_inp.scale | 0x27cf40a0 | 0x2c00 | | 37 | blk.1.ffn_gate_inp.weight | 0x27cf6ca0 | 0x160000 | | 38 | blk.1.ffn_gate_up_exps.weight | 0x27e56ca0 | 0x5e88000 | | 39 | blk.1.ffn_norm.weight | 0x2dcdeca0 | 0x2c00 | | 40 | blk.1.ffn_up.weight | 0x2dce18a0 | 0x11b980 | | 41 | blk.1.layer_output_scale.weight | 0x2ddfd220 | 0x4 | | 42 | blk.1.post_attention_norm.weight | 0x2ddfd240 | 0x2c00 | | 43 | blk.1.post_ffw_norm.weight | 0x2ddffe40 | 0x2c00 | | 44 | blk.1.post_ffw_norm_1.weight | 0x2de02a40 | 0x2c00 | | 45 | blk.1.post_ffw_norm_2.weight | 0x2de05640 | 0x2c00 | | 46 | blk.1.pre_ffw_norm_2.weight | 0x2de08240 | 0x2c00 | | 47 | blk.2.attn_k.weight | 0x2de0ae40 | 0x113000 | | 48 | blk.2.attn_k_norm.weight | 0x2df1de40 | 0x400 | | 49 | blk.2.attn_norm.weight | 0x2df1e240 | 0x2c00 | | 50 | blk.2.attn_output.weight | 0x2df20e40 | 0x226000 | | 51 | blk.2.attn_q.weight | 0x2e146e40 | 0x226000 | | 52 | blk.2.attn_q_norm.weight | 0x2e36ce40 | 0x400 | | 53 | blk.2.attn_v.weight | 0x2e36d240 | 0x113000 | | 54 | blk.2.ffn_down.weight | 0x2e480240 | 0x330c00 | | 55 | blk.2.ffn_down_exps.scale | 0x2e7b0e40 | 0x200 | | 56 | blk.2.ffn_down_exps.weight | 0x2e7b1040 | 0x8820000 | | 57 | blk.2.ffn_gate.weight | 0x36fd1040 | 0x11b980 | | 58 | blk.2.ffn_gate_inp.scale | 0x370ec9c0 | 0x2c00 | | 59 | blk.2.ffn_gate_inp.weight | 0x370ef5c0 | 0x160000 | | 60 | blk.2.ffn_gate_up_exps.weight | 0x3724f5c0 | 0x5e88000 | | 61 | blk.2.ffn_norm.weight | 0x3d0d75c0 | 0x2c00 | | 62 | blk.2.ffn_up.weight | 0x3d0da1c0 | 0x11b980 | | 63 | blk.2.layer_output_scale.weight | 0x3d1f5b40 | 0x4 | | 64 | blk.2.post_attention_norm.weight | 0x3d1f5b60 | 0x2c00 | | 65 | blk.2.post_ffw_norm.weight | 0x3d1f8760 | 0x2c00 | | 66 | blk.2.post_ffw_norm_1.weight | 0x3d1fb360 | 0x2c00 | | 67 | blk.2.post_ffw_norm_2.weight | 0x3d1fdf60 | 0x2c00 | | 68 | blk.2.pre_ffw_norm_2.weight | 0x3d200b60 | 0x2c00 | | 69 | blk.3.attn_k.weight | 0x3d203760 | 0x113000 | | 70 | blk.3.attn_k_norm.weight | 0x3d316760 | 0x400 | | 71 | blk.3.attn_norm.weight | 0x3d316b60 | 0x2c00 | | 72 | blk.3.attn_output.weight | 0x3d319760 | 0x226000 | | 73 | blk.3.attn_q.weight | 0x3d53f760 | 0x226000 | | 74 | blk.3.attn_q_norm.weight | 0x3d765760 | 0x400 | | 75 | blk.3.attn_v.weight | 0x3d765b60 | 0x113000 | | 76 | blk.3.ffn_down.weight | 0x3d878b60 | 0x330c00 | | 77 | blk.3.ffn_down_exps.scale | 0x3dba9760 | 0x200 | | 78 | blk.3.ffn_down_exps.weight | 0x3dba9960 | 0x8820000 | | 79 | blk.3.ffn_gate.weight | 0x463c9960 | 0x11b980 | | 80 | blk.3.ffn_gate_inp.scale | 0x464e52e0 | 0x2c00 | | 81 | blk.3.ffn_gate_inp.weight | 0x464e7ee0 | 0x160000 | | 82 | blk.3.ffn_gate_up_exps.weight | 0x46647ee0 | 0x5e88000 | | 83 | blk.3.ffn_norm.weight | 0x4c4cfee0 | 0x2c00 | | 84 | blk.3.ffn_up.weight | 0x4c4d2ae0 | 0x11b980 | | 85 | blk.3.layer_output_scale.weight | 0x4c5ee460 | 0x4 | | 86 | blk.3.post_attention_norm.weight | 0x4c5ee480 | 0x2c00 | | 87 | blk.3.post_ffw_norm.weight | 0x4c5f1080 | 0x2c00 | | 88 | blk.3.post_ffw_norm_1.weight | 0x4c5f3c80 | 0x2c00 | | 89 | blk.3.post_ffw_norm_2.weight | 0x4c5f6880 | 0x2c00 | | 90 | blk.3.pre_ffw_norm_2.weight | 0x4c5f9480 | 0x2c00 | | 91 | blk.4.attn_k.weight | 0x4c5fc080 | 0x113000 | | 92 | blk.4.attn_k_norm.weight | 0x4c70f080 | 0x400 | | 93 | blk.4.attn_norm.weight | 0x4c70f480 | 0x2c00 | | 94 | blk.4.attn_output.weight | 0x4c712080 | 0x226000 | | 95 | blk.4.attn_q.weight | 0x4c938080 | 0x226000 | | 96 | blk.4.attn_q_norm.weight | 0x4cb5e080 | 0x400 | | 97 | blk.4.attn_v.weight | 0x4cb5e480 | 0x113000 | | 98 | blk.4.ffn_down.weight | 0x4cc71480 | 0x330c00 | | 99 | blk.4.ffn_down_exps.scale | 0x4cfa2080 | 0x200 | | 100 | blk.4.ffn_down_exps.weight | 0x4cfa2280 | 0x8820000 | | 101 | blk.4.ffn_gate.weight | 0x557c2280 | 0x11b980 | | 102 | blk.4.ffn_gate_inp.scale | 0x558ddc00 | 0x2c00 | | 103 | blk.4.ffn_gate_inp.weight | 0x558e0800 | 0x160000 | | 104 | blk.4.ffn_gate_up_exps.weight | 0x55a40800 | 0x5e88000 | | 105 | blk.4.ffn_norm.weight | 0x5b8c8800 | 0x2c00 | | 106 | blk.4.ffn_up.weight | 0x5b8cb400 | 0x11b980 | | 107 | blk.4.layer_output_scale.weight | 0x5b9e6d80 | 0x4 | | 108 | blk.4.post_attention_norm.weight | 0x5b9e6da0 | 0x2c00 | | 109 | blk.4.post_ffw_norm.weight | 0x5b9e99a0 | 0x2c00 | | 110 | blk.4.post_ffw_norm_1.weight | 0x5b9ec5a0 | 0x2c00 | | 111 | blk.4.post_ffw_norm_2.weight | 0x5b9ef1a0 | 0x2c00 | | 112 | blk.4.pre_ffw_norm_2.weight | 0x5b9f1da0 | 0x2c00 | | 113 | blk.5.attn_k.weight | 0x5b9f49a0 | 0x89800 | | 114 | blk.5.attn_k_norm.weight | 0x5ba7e1a0 | 0x800 | | 115 | blk.5.attn_norm.weight | 0x5ba7e9a0 | 0x2c00 | | 116 | blk.5.attn_output.weight | 0x5ba815a0 | 0x44c000 | | 117 | blk.5.attn_q.weight | 0x5becd5a0 | 0x44c000 | | 118 | blk.5.attn_q_norm.weight | 0x5c3195a0 | 0x800 | | 119 | blk.5.ffn_down.weight | 0x5c319da0 | 0x330c00 | | 120 | blk.5.ffn_down_exps.scale | 0x5c64a9a0 | 0x200 | | 121 | blk.5.ffn_down_exps.weight | 0x5c64aba0 | 0x8820000 | | 122 | blk.5.ffn_gate.weight | 0x64e6aba0 | 0x11b980 | | 123 | blk.5.ffn_gate_inp.scale | 0x64f86520 | 0x2c00 | | 124 | blk.5.ffn_gate_inp.weight | 0x64f89120 | 0x160000 | | 125 | blk.5.ffn_gate_up_exps.weight | 0x650e9120 | 0x5e88000 | | 126 | blk.5.ffn_norm.weight | 0x6af71120 | 0x2c00 | | 127 | blk.5.ffn_up.weight | 0x6af73d20 | 0x11b980 | | 128 | blk.5.layer_output_scale.weight | 0x6b08f6a0 | 0x4 | | 129 | blk.5.post_attention_norm.weight | 0x6b08f6c0 | 0x2c00 | | 130 | blk.5.post_ffw_norm.weight | 0x6b0922c0 | 0x2c00 | | 131 | blk.5.post_ffw_norm_1.weight | 0x6b094ec0 | 0x2c00 | | 132 | blk.5.post_ffw_norm_2.weight | 0x6b097ac0 | 0x2c00 | | 133 | blk.5.pre_ffw_norm_2.weight | 0x6b09a6c0 | 0x2c00 | | 134 | blk.6.attn_k.weight | 0x6b09d2c0 | 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blk.6.post_ffw_norm.weight | 0x7a48abe0 | 0x2c00 | | 153 | blk.6.post_ffw_norm_1.weight | 0x7a48d7e0 | 0x2c00 | | 154 | blk.6.post_ffw_norm_2.weight | 0x7a4903e0 | 0x2c00 | | 155 | blk.6.pre_ffw_norm_2.weight | 0x7a492fe0 | 0x2c00 | | 156 | blk.7.attn_k.weight | 0x7a495be0 | 0x113000 | | 157 | blk.7.attn_k_norm.weight | 0x7a5a8be0 | 0x400 | | 158 | blk.7.attn_norm.weight | 0x7a5a8fe0 | 0x2c00 | | 159 | blk.7.attn_output.weight | 0x7a5abbe0 | 0x226000 | | 160 | blk.7.attn_q.weight | 0x7a7d1be0 | 0x226000 | | 161 | blk.7.attn_q_norm.weight | 0x7a9f7be0 | 0x400 | | 162 | blk.7.attn_v.weight | 0x7a9f7fe0 | 0x113000 | | 163 | blk.7.ffn_down.weight | 0x7ab0afe0 | 0x330c00 | | 164 | blk.7.ffn_down_exps.scale | 0x7ae3bbe0 | 0x200 | | 165 | blk.7.ffn_down_exps.weight | 0x7ae3bde0 | 0x8820000 | | 166 | blk.7.ffn_gate.weight | 0x8365bde0 | 0x11b980 | | 167 | blk.7.ffn_gate_inp.scale | 0x83777760 | 0x2c00 | | 168 | blk.7.ffn_gate_inp.weight | 0x8377a360 | 0x160000 | | 169 | 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0x11b980 | | 604 | blk.27.ffn_gate_inp.scale | 0x1b4ef2de0 | 0x2c00 | | 605 | blk.27.ffn_gate_inp.weight | 0x1b4ef59e0 | 0x160000 | | 606 | blk.27.ffn_gate_up_exps.weight | 0x1b50559e0 | 0x5e88000 | | 607 | blk.27.ffn_norm.weight | 0x1baedd9e0 | 0x2c00 | | 608 | blk.27.ffn_up.weight | 0x1baee05e0 | 0x11b980 | | 609 | blk.27.layer_output_scale.weight | 0x1baffbf60 | 0x4 | | 610 | blk.27.post_attention_norm.weight | 0x1baffbf80 | 0x2c00 | | 611 | blk.27.post_ffw_norm.weight | 0x1baffeb80 | 0x2c00 | | 612 | blk.27.post_ffw_norm_1.weight | 0x1bb001780 | 0x2c00 | | 613 | blk.27.post_ffw_norm_2.weight | 0x1bb004380 | 0x2c00 | | 614 | blk.27.pre_ffw_norm_2.weight | 0x1bb006f80 | 0x2c00 | | 615 | blk.28.attn_k.weight | 0x1bb009b80 | 0x113000 | | 616 | blk.28.attn_k_norm.weight | 0x1bb11cb80 | 0x400 | | 617 | blk.28.attn_norm.weight | 0x1bb11cf80 | 0x2c00 | | 618 | blk.28.attn_output.weight | 0x1bb11fb80 | 0x226000 | | 619 | blk.28.attn_q.weight | 0x1bb345b80 | 0x226000 | | 620 | blk.28.attn_q_norm.weight | 0x1bb56bb80 | 0x400 | | 621 | blk.28.attn_v.weight | 0x1bb56bf80 | 0x113000 | | 622 | blk.28.ffn_down.weight | 0x1bb67ef80 | 0x330c00 | | 623 | blk.28.ffn_down_exps.scale | 0x1bb9afb80 | 0x200 | | 624 | blk.28.ffn_down_exps.weight | 0x1bb9afd80 | 0x8820000 | | 625 | blk.28.ffn_gate.weight | 0x1c41cfd80 | 0x11b980 | | 626 | blk.28.ffn_gate_inp.scale | 0x1c42eb700 | 0x2c00 | | 627 | blk.28.ffn_gate_inp.weight | 0x1c42ee300 | 0x160000 | | 628 | blk.28.ffn_gate_up_exps.weight | 0x1c444e300 | 0x5e88000 | | 629 | blk.28.ffn_norm.weight | 0x1ca2d6300 | 0x2c00 | | 630 | blk.28.ffn_up.weight | 0x1ca2d8f00 | 0x11b980 | | 631 | blk.28.layer_output_scale.weight | 0x1ca3f4880 | 0x4 | | 632 | blk.28.post_attention_norm.weight | 0x1ca3f48a0 | 0x2c00 | | 633 | blk.28.post_ffw_norm.weight | 0x1ca3f74a0 | 0x2c00 | | 634 | blk.28.post_ffw_norm_1.weight | 0x1ca3fa0a0 | 0x2c00 | | 635 | blk.28.post_ffw_norm_2.weight | 0x1ca3fcca0 | 0x2c00 | | 636 | blk.28.pre_ffw_norm_2.weight | 0x1ca3ff8a0 | 0x2c00 | | 637 | blk.29.attn_k.weight | 0x1ca4024a0 | 0x89800 | | 638 | blk.29.attn_k_norm.weight | 0x1ca48bca0 | 0x800 | | 639 | blk.29.attn_norm.weight | 0x1ca48c4a0 | 0x2c00 | | 640 | blk.29.attn_output.weight | 0x1ca48f0a0 | 0x44c000 | | 641 | blk.29.attn_q.weight | 0x1ca8db0a0 | 0x44c000 | | 642 | blk.29.attn_q_norm.weight | 0x1cad270a0 | 0x800 | | 643 | blk.29.ffn_down.weight | 0x1cad278a0 | 0x330c00 | | 644 | blk.29.ffn_down_exps.scale | 0x1cb0584a0 | 0x200 | | 645 | blk.29.ffn_down_exps.weight | 0x1cb0586a0 | 0x8820000 | | 646 | blk.29.ffn_gate.weight | 0x1d38786a0 | 0x11b980 | | 647 | blk.29.ffn_gate_inp.scale | 0x1d3994020 | 0x2c00 | | 648 | blk.29.ffn_gate_inp.weight | 0x1d3996c20 | 0x160000 | | 649 | blk.29.ffn_gate_up_exps.weight | 0x1d3af6c20 | 0x5e88000 | | 650 | blk.29.ffn_norm.weight | 0x1d997ec20 | 0x2c00 | | 651 | blk.29.ffn_up.weight | 0x1d9981820 | 0x11b980 | | 652 | blk.29.layer_output_scale.weight | 0x1d9a9d1a0 | 0x4 | | 653 | blk.29.post_attention_norm.weight | 0x1d9a9d1c0 | 0x2c00 | | 654 | blk.29.post_ffw_norm.weight | 0x1d9a9fdc0 | 0x2c00 | | 655 | blk.29.post_ffw_norm_1.weight | 0x1d9aa29c0 | 0x2c00 | | 656 | blk.29.post_ffw_norm_2.weight | 0x1d9aa55c0 | 0x2c00 | | 657 | blk.29.pre_ffw_norm_2.weight | 0x1d9aa81c0 | 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 | Q2_K | 2.6250 | - Total elements in base: (~738M) 738200576 - Percentage of total elements: 2.93% - Bits per Weight (BPW) for base: 2.6251 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 7 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 29 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 51 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 73 | blk.3.attn_q.weight | Block 3 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 95 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 117 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~23M) 23068672 | 2816 x 8192 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.4974 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 138 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 160 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 182 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 204 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 226 | blk.10.attn_q.weight | Block 10 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 248 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~23M) 23068672 | 2816 x 8192 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.4974 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 269 | blk.12.attn_q.weight | Block 12 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 291 | blk.13.attn_q.weight | Block 13 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 313 | blk.14.attn_q.weight | Block 14 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 335 | blk.15.attn_q.weight | Block 15 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 357 | blk.16.attn_q.weight | Block 16 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 379 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~23M) 23068672 | 2816 x 8192 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.4974 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 400 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 422 | blk.19.attn_q.weight | Block 19 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 444 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 466 | blk.21.attn_q.weight | Block 21 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 488 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 510 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~23M) 23068672 | 2816 x 8192 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.4974 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 531 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 553 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 575 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 597 | blk.27.attn_q.weight | Block 27 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 619 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~12M) 11534336 | 2816 x 4096 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.5139 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 641 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~23M) 23068672 | 2816 x 8192 x 1 x 1 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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 | IQ1_S | 1.5625 | | 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: 2.4974 bits Total BPW for gemma-4-26B-A4B-it-Q2_K.gguf: 2.5145 bits