Instructions to use eaddario/gemma-4-E4B-it-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use eaddario/gemma-4-E4B-it-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf eaddario/gemma-4-E4B-it-GGUF:F16 # Run inference directly in the terminal: llama cli -hf eaddario/gemma-4-E4B-it-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf eaddario/gemma-4-E4B-it-GGUF:F16 # Run inference directly in the terminal: llama cli -hf eaddario/gemma-4-E4B-it-GGUF:F16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf eaddario/gemma-4-E4B-it-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf eaddario/gemma-4-E4B-it-GGUF:F16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf eaddario/gemma-4-E4B-it-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf eaddario/gemma-4-E4B-it-GGUF:F16
Use Docker
docker model run hf.co/eaddario/gemma-4-E4B-it-GGUF:F16
- LM Studio
- Jan
- Ollama
How to use eaddario/gemma-4-E4B-it-GGUF with Ollama:
ollama run hf.co/eaddario/gemma-4-E4B-it-GGUF:F16
- Unsloth Desktop
- Pi
How to use eaddario/gemma-4-E4B-it-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf eaddario/gemma-4-E4B-it-GGUF:F16
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "eaddario/gemma-4-E4B-it-GGUF:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use eaddario/gemma-4-E4B-it-GGUF with Docker Model Runner:
docker model run hf.co/eaddario/gemma-4-E4B-it-GGUF:F16
- Lemonade
How to use eaddario/gemma-4-E4B-it-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull eaddario/gemma-4-E4B-it-GGUF:F16
Run and chat with the model
lemonade run user.gemma-4-E4B-it-GGUF-F16
List all available models
lemonade list
- Hermes Agent
How to use eaddario/gemma-4-E4B-it-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf eaddario/gemma-4-E4B-it-GGUF:F16
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default eaddario/gemma-4-E4B-it-GGUF:F16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use eaddario/gemma-4-E4B-it-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf eaddario/gemma-4-E4B-it-GGUF:F16
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "eaddario/gemma-4-E4B-it-GGUF:F16" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
File size: 203,671 Bytes
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- Endian: LITTLE endian
## Key Value Metadata Store
There are 48 key-value pairs in this file
| POS | TYPE | Count | Key | Value |
| ---: | :-------- | -----: | :-------------------------------------- | :--------------------------------------------------------------------------------------------------------------- |
| 1 | UINT32 | 1 | GGUF.version | 3 |
| 2 | UINT64 | 1 | GGUF.tensor_count | 720 |
| 3 | UINT64 | 1 | GGUF.kv_count | 45 |
| 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 E4B It` |
| 10 | STRING | 1 | general.size_label | `7.5B` |
| 11 | STRING | 1 | general.license | `apache-2.0` |
| 12 | STRING | 1 | general.license.link | `https://ai.google.dev/gemma/docs/gemma_4_license` |
| 13 | [STRING] | 1 | general.tags | [ `any-to-any` ] |
| 14 | UINT32 | 1 | gemma4.block_count | 42 |
| 15 | UINT32 | 1 | gemma4.context_length | 131072 |
| 16 | UINT32 | 1 | gemma4.embedding_length | 2560 |
| 17 | UINT32 | 1 | gemma4.feed_forward_length | 10240 |
| 18 | UINT32 | 1 | gemma4.attention.head_count | 8 |
| 19 | UINT32 | 1 | gemma4.attention.head_count_kv | 2 |
| 20 | FLOAT32 | 1 | gemma4.rope.freq_base | 1e+06 |
| 21 | FLOAT32 | 1 | gemma4.rope.freq_base_swa | 10000.0 |
| 22 | FLOAT32 | 1 | gemma4.attention.layer_norm_rms_epsilon | 1e-06 |
| 23 | UINT32 | 1 | gemma4.attention.key_length | 512 |
| 24 | UINT32 | 1 | gemma4.attention.value_length | 512 |
| 25 | UINT32 | 1 | general.file_type | 1 |
| 26 | FLOAT32 | 1 | gemma4.final_logit_softcapping | 30.0 |
| 27 | UINT32 | 1 | gemma4.attention.sliding_window | 512 |
| 28 | UINT32 | 1 | gemma4.attention.shared_kv_layers | 18 |
| 29 | UINT32 | 1 | gemma4.embedding_length_per_layer_input | 256 |
| 30 | [BOOL] | 42 | gemma4.attention.sliding_window_pattern | [ True, True, True, True, True, False, True, ... ] |
| 31 | UINT32 | 1 | gemma4.attention.key_length_swa | 256 |
| 32 | UINT32 | 1 | gemma4.attention.value_length_swa | 256 |
| 33 | UINT32 | 1 | gemma4.rope.dimension_count | 512 |
| 34 | UINT32 | 1 | gemma4.rope.dimension_count_swa | 256 |
| 35 | UINT32 | 1 | general.quantization_version | 2 |
| 36 | STRING | 1 | tokenizer.ggml.model | `gemma4` |
| 37 | [STRING] | 262144 | tokenizer.ggml.tokens | [ `<pad>`, `<eos>`, `<bos>`, `<unk>`, `<mask>`, ... ] |
| 38 | [FLOAT32] | 262144 | tokenizer.ggml.scores | [ -1000.0, -1000.0, -1000.0, -1000.0, -1000.0, -1000.0, -1000.0, ... ] |
| 39 | [INT32] | 262144 | tokenizer.ggml.token_type | [ 3, 3, 3, 3, 3, 1, 1, ... ] |
| 40 | [STRING] | 514906 | tokenizer.ggml.merges | [ ``...``, `▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁`...`▁▁▁▁▁▁▁▁▁▁▁▁▁ ▁`, ``...``, ``...``, `▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁`...`▁▁▁▁▁▁▁▁▁▁▁▁ ▁▁`, ... ] |
| 41 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 2 |
| 42 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 1 |
| 43 | UINT32 | 1 | tokenizer.ggml.unknown_token_id | 3 |
| 44 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 0 |
| 45 | UINT32 | 1 | tokenizer.ggml.mask_token_id | 4 |
| 46 | STRING | 1 | tokenizer.chat_template | `{%- macro format_parameters(pr`...` {%- endif -%} {%- endif -%}` |
| 47 | BOOL | 1 | tokenizer.ggml.add_space_prefix | False |
| 48 | BOOL | 1 | tokenizer.ggml.add_bos_token | True |
## Tensors Overview ~8B Elements
Total number of elements in all tensors: 7518069290 Elements
- [gemma-4-E4B-it-F16.gguf - GGUF Internal File Dump](#gemma-4-e4b-it-f16gguf---gguf-internal-file-dump)
- [Key Value Metadata Store](#key-value-metadata-store)
- [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
- [Tensor Data Offset](#tensor-data-offset)
- [Base Tensor Group : ~4B Elements](#base-tensor-group--4b-elements)
- [Block 0 Tensor Group : ~93M Elements](#block-0-tensor-group--93m-elements)
- [Block 1 Tensor Group : ~93M Elements](#block-1-tensor-group--93m-elements)
- [Block 10 Tensor Group : ~93M Elements](#block-10-tensor-group--93m-elements)
- [Block 11 Tensor Group : ~106M Elements](#block-11-tensor-group--106m-elements)
- [Block 12 Tensor Group : ~93M Elements](#block-12-tensor-group--93m-elements)
- [Block 13 Tensor Group : ~93M Elements](#block-13-tensor-group--93m-elements)
- [Block 14 Tensor Group : ~93M Elements](#block-14-tensor-group--93m-elements)
- [Block 15 Tensor Group : ~93M Elements](#block-15-tensor-group--93m-elements)
- [Block 16 Tensor Group : ~93M Elements](#block-16-tensor-group--93m-elements)
- [Block 17 Tensor Group : ~106M Elements](#block-17-tensor-group--106m-elements)
- [Block 18 Tensor Group : ~93M Elements](#block-18-tensor-group--93m-elements)
- [Block 19 Tensor Group : ~93M Elements](#block-19-tensor-group--93m-elements)
- [Block 2 Tensor Group : ~93M Elements](#block-2-tensor-group--93m-elements)
- [Block 20 Tensor Group : ~93M Elements](#block-20-tensor-group--93m-elements)
- [Block 21 Tensor Group : ~93M Elements](#block-21-tensor-group--93m-elements)
- [Block 22 Tensor Group : ~93M Elements](#block-22-tensor-group--93m-elements)
- [Block 23 Tensor Group : ~106M Elements](#block-23-tensor-group--106m-elements)
- [Block 24 Tensor Group : ~93M Elements](#block-24-tensor-group--93m-elements)
- [Block 25 Tensor Group : ~93M Elements](#block-25-tensor-group--93m-elements)
- [Block 26 Tensor Group : ~93M Elements](#block-26-tensor-group--93m-elements)
- [Block 27 Tensor Group : ~93M Elements](#block-27-tensor-group--93m-elements)
- [Block 28 Tensor Group : ~93M Elements](#block-28-tensor-group--93m-elements)
- [Block 29 Tensor Group : ~106M Elements](#block-29-tensor-group--106m-elements)
- [Block 3 Tensor Group : ~93M Elements](#block-3-tensor-group--93m-elements)
- [Block 30 Tensor Group : ~93M Elements](#block-30-tensor-group--93m-elements)
- [Block 31 Tensor Group : ~93M Elements](#block-31-tensor-group--93m-elements)
- [Block 32 Tensor Group : ~93M Elements](#block-32-tensor-group--93m-elements)
- [Block 33 Tensor Group : ~93M Elements](#block-33-tensor-group--93m-elements)
- [Block 34 Tensor Group : ~93M Elements](#block-34-tensor-group--93m-elements)
- [Block 35 Tensor Group : ~106M Elements](#block-35-tensor-group--106m-elements)
- [Block 36 Tensor Group : ~93M Elements](#block-36-tensor-group--93m-elements)
- [Block 37 Tensor Group : ~93M Elements](#block-37-tensor-group--93m-elements)
- [Block 38 Tensor Group : ~93M Elements](#block-38-tensor-group--93m-elements)
- [Block 39 Tensor Group : ~93M Elements](#block-39-tensor-group--93m-elements)
- [Block 4 Tensor Group : ~93M Elements](#block-4-tensor-group--93m-elements)
- [Block 40 Tensor Group : ~93M Elements](#block-40-tensor-group--93m-elements)
- [Block 41 Tensor Group : ~106M Elements](#block-41-tensor-group--106m-elements)
- [Block 5 Tensor Group : ~106M Elements](#block-5-tensor-group--106m-elements)
- [Block 6 Tensor Group : ~93M Elements](#block-6-tensor-group--93m-elements)
- [Block 7 Tensor Group : ~93M Elements](#block-7-tensor-group--93m-elements)
- [Block 8 Tensor Group : ~93M Elements](#block-8-tensor-group--93m-elements)
- [Block 9 Tensor Group : ~93M Elements](#block-9-tensor-group--93m-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 | rope_freqs.weight | 0xf172c0 | 0x400 |
| 1 | token_embd.weight | 0xf176c0 | 0x50000000 |
| 2 | per_layer_token_embd.weight | 0x50f176c0 | 0x150000000 |
| 3 | blk.0.attn_norm.weight | 0x1a0f176c0 | 0x2800 |
| 4 | blk.0.layer_output_scale.weight | 0x1a0f19ec0 | 0x4 |
| 5 | blk.0.ffn_down.weight | 0x1a0f19ee0 | 0x3200000 |
| 6 | blk.0.ffn_gate.weight | 0x1a4119ee0 | 0x3200000 |
| 7 | blk.0.ffn_up.weight | 0x1a7319ee0 | 0x3200000 |
| 8 | blk.0.inp_gate.weight | 0x1aa519ee0 | 0x140000 |
| 9 | blk.0.proj.weight | 0x1aa659ee0 | 0x140000 |
| 10 | blk.0.post_attention_norm.weight | 0x1aa799ee0 | 0x2800 |
| 11 | blk.0.post_ffw_norm.weight | 0x1aa79c6e0 | 0x2800 |
| 12 | blk.0.post_norm.weight | 0x1aa79eee0 | 0x2800 |
| 13 | blk.0.ffn_norm.weight | 0x1aa7a16e0 | 0x2800 |
| 14 | blk.0.attn_k_norm.weight | 0x1aa7a3ee0 | 0x400 |
| 15 | blk.0.attn_k.weight | 0x1aa7a42e0 | 0x280000 |
| 16 | blk.0.attn_output.weight | 0x1aaa242e0 | 0xa00000 |
| 17 | blk.0.attn_q_norm.weight | 0x1ab4242e0 | 0x400 |
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| 555 | blk.38.post_ffw_norm.weight | 0x31563f2e0 | 0x2800 |
| 556 | blk.38.post_norm.weight | 0x315641ae0 | 0x2800 |
| 557 | blk.38.ffn_norm.weight | 0x3156442e0 | 0x2800 |
| 558 | blk.38.attn_k_norm.weight | 0x315646ae0 | 0x400 |
| 559 | blk.38.attn_k.weight | 0x315646ee0 | 0x280000 |
| 560 | blk.38.attn_output.weight | 0x3158c6ee0 | 0xa00000 |
| 561 | blk.38.attn_q_norm.weight | 0x3162c6ee0 | 0x400 |
| 562 | blk.38.attn_q.weight | 0x3162c72e0 | 0xa00000 |
| 563 | blk.38.attn_v.weight | 0x316cc72e0 | 0x280000 |
| 564 | blk.39.attn_norm.weight | 0x316f472e0 | 0x2800 |
| 565 | blk.39.layer_output_scale.weight | 0x316f49ae0 | 0x4 |
| 566 | blk.39.ffn_down.weight | 0x316f49b00 | 0x3200000 |
| 567 | blk.39.ffn_gate.weight | 0x31a149b00 | 0x3200000 |
| 568 | blk.39.ffn_up.weight | 0x31d349b00 | 0x3200000 |
| 569 | blk.39.inp_gate.weight | 0x320549b00 | 0x140000 |
| 570 | blk.39.proj.weight | 0x320689b00 | 0x140000 |
| 571 | blk.39.post_attention_norm.weight | 0x3207c9b00 | 0x2800 |
| 572 | blk.39.post_ffw_norm.weight | 0x3207cc300 | 0x2800 |
| 573 | blk.39.post_norm.weight | 0x3207ceb00 | 0x2800 |
| 574 | blk.39.ffn_norm.weight | 0x3207d1300 | 0x2800 |
| 575 | blk.39.attn_k_norm.weight | 0x3207d3b00 | 0x400 |
| 576 | blk.39.attn_k.weight | 0x3207d3f00 | 0x280000 |
| 577 | blk.39.attn_output.weight | 0x320a53f00 | 0xa00000 |
| 578 | blk.39.attn_q_norm.weight | 0x321453f00 | 0x400 |
| 579 | blk.39.attn_q.weight | 0x321454300 | 0xa00000 |
| 580 | blk.39.attn_v.weight | 0x321e54300 | 0x280000 |
| 581 | blk.4.attn_norm.weight | 0x3220d4300 | 0x2800 |
| 582 | blk.4.layer_output_scale.weight | 0x3220d6b00 | 0x4 |
| 583 | blk.4.ffn_down.weight | 0x3220d6b20 | 0x3200000 |
| 584 | blk.4.ffn_gate.weight | 0x3252d6b20 | 0x3200000 |
| 585 | blk.4.ffn_up.weight | 0x3284d6b20 | 0x3200000 |
| 586 | blk.4.inp_gate.weight | 0x32b6d6b20 | 0x140000 |
| 587 | blk.4.proj.weight | 0x32b816b20 | 0x140000 |
| 588 | blk.4.post_attention_norm.weight | 0x32b956b20 | 0x2800 |
| 589 | blk.4.post_ffw_norm.weight | 0x32b959320 | 0x2800 |
| 590 | blk.4.post_norm.weight | 0x32b95bb20 | 0x2800 |
| 591 | blk.4.ffn_norm.weight | 0x32b95e320 | 0x2800 |
| 592 | blk.4.attn_k_norm.weight | 0x32b960b20 | 0x400 |
| 593 | blk.4.attn_k.weight | 0x32b960f20 | 0x280000 |
| 594 | blk.4.attn_output.weight | 0x32bbe0f20 | 0xa00000 |
| 595 | blk.4.attn_q_norm.weight | 0x32c5e0f20 | 0x400 |
| 596 | blk.4.attn_q.weight | 0x32c5e1320 | 0xa00000 |
| 597 | blk.4.attn_v.weight | 0x32cfe1320 | 0x280000 |
| 598 | blk.40.attn_norm.weight | 0x32d261320 | 0x2800 |
| 599 | blk.40.layer_output_scale.weight | 0x32d263b20 | 0x4 |
| 600 | blk.40.ffn_down.weight | 0x32d263b40 | 0x3200000 |
| 601 | blk.40.ffn_gate.weight | 0x330463b40 | 0x3200000 |
| 602 | blk.40.ffn_up.weight | 0x333663b40 | 0x3200000 |
| 603 | blk.40.inp_gate.weight | 0x336863b40 | 0x140000 |
| 604 | blk.40.proj.weight | 0x3369a3b40 | 0x140000 |
| 605 | blk.40.post_attention_norm.weight | 0x336ae3b40 | 0x2800 |
| 606 | blk.40.post_ffw_norm.weight | 0x336ae6340 | 0x2800 |
| 607 | blk.40.post_norm.weight | 0x336ae8b40 | 0x2800 |
| 608 | blk.40.ffn_norm.weight | 0x336aeb340 | 0x2800 |
| 609 | blk.40.attn_k_norm.weight | 0x336aedb40 | 0x400 |
| 610 | blk.40.attn_k.weight | 0x336aedf40 | 0x280000 |
| 611 | blk.40.attn_output.weight | 0x336d6df40 | 0xa00000 |
| 612 | blk.40.attn_q_norm.weight | 0x33776df40 | 0x400 |
| 613 | blk.40.attn_q.weight | 0x33776e340 | 0xa00000 |
| 614 | blk.40.attn_v.weight | 0x33816e340 | 0x280000 |
| 615 | blk.41.attn_norm.weight | 0x3383ee340 | 0x2800 |
| 616 | blk.41.layer_output_scale.weight | 0x3383f0b40 | 0x4 |
| 617 | blk.41.ffn_down.weight | 0x3383f0b60 | 0x3200000 |
| 618 | blk.41.ffn_gate.weight | 0x33b5f0b60 | 0x3200000 |
| 619 | blk.41.ffn_up.weight | 0x33e7f0b60 | 0x3200000 |
| 620 | blk.41.inp_gate.weight | 0x3419f0b60 | 0x140000 |
| 621 | blk.41.proj.weight | 0x341b30b60 | 0x140000 |
| 622 | blk.41.post_attention_norm.weight | 0x341c70b60 | 0x2800 |
| 623 | blk.41.post_ffw_norm.weight | 0x341c73360 | 0x2800 |
| 624 | blk.41.post_norm.weight | 0x341c75b60 | 0x2800 |
| 625 | blk.41.ffn_norm.weight | 0x341c78360 | 0x2800 |
| 626 | blk.41.attn_k_norm.weight | 0x341c7ab60 | 0x800 |
| 627 | blk.41.attn_k.weight | 0x341c7b360 | 0x500000 |
| 628 | blk.41.attn_output.weight | 0x34217b360 | 0x1400000 |
| 629 | blk.41.attn_q_norm.weight | 0x34357b360 | 0x800 |
| 630 | blk.41.attn_q.weight | 0x34357bb60 | 0x1400000 |
| 631 | blk.41.attn_v.weight | 0x34497bb60 | 0x500000 |
| 632 | blk.5.attn_norm.weight | 0x344e7bb60 | 0x2800 |
| 633 | blk.5.layer_output_scale.weight | 0x344e7e360 | 0x4 |
| 634 | blk.5.ffn_down.weight | 0x344e7e380 | 0x3200000 |
| 635 | blk.5.ffn_gate.weight | 0x34807e380 | 0x3200000 |
| 636 | blk.5.ffn_up.weight | 0x34b27e380 | 0x3200000 |
| 637 | blk.5.inp_gate.weight | 0x34e47e380 | 0x140000 |
| 638 | blk.5.proj.weight | 0x34e5be380 | 0x140000 |
| 639 | blk.5.post_attention_norm.weight | 0x34e6fe380 | 0x2800 |
| 640 | blk.5.post_ffw_norm.weight | 0x34e700b80 | 0x2800 |
| 641 | blk.5.post_norm.weight | 0x34e703380 | 0x2800 |
| 642 | blk.5.ffn_norm.weight | 0x34e705b80 | 0x2800 |
| 643 | blk.5.attn_k_norm.weight | 0x34e708380 | 0x800 |
| 644 | blk.5.attn_k.weight | 0x34e708b80 | 0x500000 |
| 645 | blk.5.attn_output.weight | 0x34ec08b80 | 0x1400000 |
| 646 | blk.5.attn_q_norm.weight | 0x350008b80 | 0x800 |
| 647 | blk.5.attn_q.weight | 0x350009380 | 0x1400000 |
| 648 | blk.5.attn_v.weight | 0x351409380 | 0x500000 |
| 649 | blk.6.attn_norm.weight | 0x351909380 | 0x2800 |
| 650 | blk.6.layer_output_scale.weight | 0x35190bb80 | 0x4 |
| 651 | blk.6.ffn_down.weight | 0x35190bba0 | 0x3200000 |
| 652 | blk.6.ffn_gate.weight | 0x354b0bba0 | 0x3200000 |
| 653 | blk.6.ffn_up.weight | 0x357d0bba0 | 0x3200000 |
| 654 | blk.6.inp_gate.weight | 0x35af0bba0 | 0x140000 |
| 655 | blk.6.proj.weight | 0x35b04bba0 | 0x140000 |
| 656 | blk.6.post_attention_norm.weight | 0x35b18bba0 | 0x2800 |
| 657 | blk.6.post_ffw_norm.weight | 0x35b18e3a0 | 0x2800 |
| 658 | blk.6.post_norm.weight | 0x35b190ba0 | 0x2800 |
| 659 | blk.6.ffn_norm.weight | 0x35b1933a0 | 0x2800 |
| 660 | blk.6.attn_k_norm.weight | 0x35b195ba0 | 0x400 |
| 661 | blk.6.attn_k.weight | 0x35b195fa0 | 0x280000 |
| 662 | blk.6.attn_output.weight | 0x35b415fa0 | 0xa00000 |
| 663 | blk.6.attn_q_norm.weight | 0x35be15fa0 | 0x400 |
| 664 | blk.6.attn_q.weight | 0x35be163a0 | 0xa00000 |
| 665 | blk.6.attn_v.weight | 0x35c8163a0 | 0x280000 |
| 666 | blk.7.attn_norm.weight | 0x35ca963a0 | 0x2800 |
| 667 | blk.7.layer_output_scale.weight | 0x35ca98ba0 | 0x4 |
| 668 | blk.7.ffn_down.weight | 0x35ca98bc0 | 0x3200000 |
| 669 | blk.7.ffn_gate.weight | 0x35fc98bc0 | 0x3200000 |
| 670 | blk.7.ffn_up.weight | 0x362e98bc0 | 0x3200000 |
| 671 | blk.7.inp_gate.weight | 0x366098bc0 | 0x140000 |
| 672 | blk.7.proj.weight | 0x3661d8bc0 | 0x140000 |
| 673 | blk.7.post_attention_norm.weight | 0x366318bc0 | 0x2800 |
| 674 | blk.7.post_ffw_norm.weight | 0x36631b3c0 | 0x2800 |
| 675 | blk.7.post_norm.weight | 0x36631dbc0 | 0x2800 |
| 676 | blk.7.ffn_norm.weight | 0x3663203c0 | 0x2800 |
| 677 | blk.7.attn_k_norm.weight | 0x366322bc0 | 0x400 |
| 678 | blk.7.attn_k.weight | 0x366322fc0 | 0x280000 |
| 679 | blk.7.attn_output.weight | 0x3665a2fc0 | 0xa00000 |
| 680 | blk.7.attn_q_norm.weight | 0x366fa2fc0 | 0x400 |
| 681 | blk.7.attn_q.weight | 0x366fa33c0 | 0xa00000 |
| 682 | blk.7.attn_v.weight | 0x3679a33c0 | 0x280000 |
| 683 | blk.8.attn_norm.weight | 0x367c233c0 | 0x2800 |
| 684 | blk.8.layer_output_scale.weight | 0x367c25bc0 | 0x4 |
| 685 | blk.8.ffn_down.weight | 0x367c25be0 | 0x3200000 |
| 686 | blk.8.ffn_gate.weight | 0x36ae25be0 | 0x3200000 |
| 687 | blk.8.ffn_up.weight | 0x36e025be0 | 0x3200000 |
| 688 | blk.8.inp_gate.weight | 0x371225be0 | 0x140000 |
| 689 | blk.8.proj.weight | 0x371365be0 | 0x140000 |
| 690 | blk.8.post_attention_norm.weight | 0x3714a5be0 | 0x2800 |
| 691 | blk.8.post_ffw_norm.weight | 0x3714a83e0 | 0x2800 |
| 692 | blk.8.post_norm.weight | 0x3714aabe0 | 0x2800 |
| 693 | blk.8.ffn_norm.weight | 0x3714ad3e0 | 0x2800 |
| 694 | blk.8.attn_k_norm.weight | 0x3714afbe0 | 0x400 |
| 695 | blk.8.attn_k.weight | 0x3714affe0 | 0x280000 |
| 696 | blk.8.attn_output.weight | 0x37172ffe0 | 0xa00000 |
| 697 | blk.8.attn_q_norm.weight | 0x37212ffe0 | 0x400 |
| 698 | blk.8.attn_q.weight | 0x3721303e0 | 0xa00000 |
| 699 | blk.8.attn_v.weight | 0x372b303e0 | 0x280000 |
| 700 | blk.9.attn_norm.weight | 0x372db03e0 | 0x2800 |
| 701 | blk.9.layer_output_scale.weight | 0x372db2be0 | 0x4 |
| 702 | blk.9.ffn_down.weight | 0x372db2c00 | 0x3200000 |
| 703 | blk.9.ffn_gate.weight | 0x375fb2c00 | 0x3200000 |
| 704 | blk.9.ffn_up.weight | 0x3791b2c00 | 0x3200000 |
| 705 | blk.9.inp_gate.weight | 0x37c3b2c00 | 0x140000 |
| 706 | blk.9.proj.weight | 0x37c4f2c00 | 0x140000 |
| 707 | blk.9.post_attention_norm.weight | 0x37c632c00 | 0x2800 |
| 708 | blk.9.post_ffw_norm.weight | 0x37c635400 | 0x2800 |
| 709 | blk.9.post_norm.weight | 0x37c637c00 | 0x2800 |
| 710 | blk.9.ffn_norm.weight | 0x37c63a400 | 0x2800 |
| 711 | blk.9.attn_k_norm.weight | 0x37c63cc00 | 0x400 |
| 712 | blk.9.attn_k.weight | 0x37c63d000 | 0x280000 |
| 713 | blk.9.attn_output.weight | 0x37c8bd000 | 0xa00000 |
| 714 | blk.9.attn_q_norm.weight | 0x37d2bd000 | 0x400 |
| 715 | blk.9.attn_q.weight | 0x37d2bd400 | 0xa00000 |
| 716 | blk.9.attn_v.weight | 0x37dcbd400 | 0x280000 |
| 717 | output_norm.weight | 0x37df3d400 | 0x2800 |
| 718 | per_layer_model_proj.weight | 0x37df3fc00 | 0x3480000 |
| 719 | per_layer_proj_norm.weight | 0x3813bfc00 | 0x400 |
### <a name="base">Base Tensor Group : ~4B Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------- | :------------------------------- | :----------------- | :--------------------- | :--- | ------: |
| 0 | rope_freqs.weight | Rope_Freqs (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 1 | token_embd.weight | Token Embedding (W) | (~671M) 671088640 | 2560 x 262144 x 1 x 1 | F16 | 16.0000 |
| 2 | per_layer_token_embd.weight | Per_Layer_Token_Embd (W) | ( ~3B) 2818572288 | 10752 x 262144 x 1 x 1 | F16 | 16.0000 |
| 717 | output_norm.weight | Output Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 718 | per_layer_model_proj.weight | Per_Layer_Model_Proj (W) | ( ~28M) 27525120 | 2560 x 10752 x 1 x 1 | F16 | 16.0000 |
| 719 | per_layer_proj_norm.weight | Per_Layer_Proj_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
- Total elements in base: ( ~4B) 3517189120
- Percentage of total elements: 46.78%
- Bits per Weight (BPW) for base: 16.0000 bits
### <a name="blk_0">Block 0 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :------------------------------- | :--------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 3 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 4 | blk.0.layer_output_scale.weight | Block 0 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 5 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 6 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 7 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 8 | blk.0.inp_gate.weight | Block 0 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 9 | blk.0.proj.weight | Block 0 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 10 | blk.0.post_attention_norm.weight | Block 0 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 11 | blk.0.post_ffw_norm.weight | Block 0 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 12 | blk.0.post_norm.weight | Block 0 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 13 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 14 | blk.0.attn_k_norm.weight | Block 0 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 15 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 16 | blk.0.attn_output.weight | Block 0 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 17 | blk.0.attn_q_norm.weight | Block 0 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 18 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 19 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.0: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.0: 16.0023 bits
### <a name="blk_1">Block 1 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :------------------------------- | :--------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 20 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 21 | blk.1.layer_output_scale.weight | Block 1 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 22 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 23 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 24 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 25 | blk.1.inp_gate.weight | Block 1 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 26 | blk.1.proj.weight | Block 1 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 27 | blk.1.post_attention_norm.weight | Block 1 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 28 | blk.1.post_ffw_norm.weight | Block 1 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 29 | blk.1.post_norm.weight | Block 1 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 30 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 31 | blk.1.attn_k_norm.weight | Block 1 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 32 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 33 | blk.1.attn_output.weight | Block 1 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 34 | blk.1.attn_q_norm.weight | Block 1 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 35 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 36 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.1: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.1: 16.0023 bits
### <a name="blk_10">Block 10 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 37 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 38 | blk.10.layer_output_scale.weight | Block 10 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 39 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 40 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 41 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 42 | blk.10.inp_gate.weight | Block 10 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 43 | blk.10.proj.weight | Block 10 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 44 | blk.10.post_attention_norm.weight | Block 10 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 45 | blk.10.post_ffw_norm.weight | Block 10 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 46 | blk.10.post_norm.weight | Block 10 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 47 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 48 | blk.10.attn_k_norm.weight | Block 10 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 49 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 50 | blk.10.attn_output.weight | Block 10 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 51 | blk.10.attn_q_norm.weight | Block 10 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 52 | blk.10.attn_q.weight | Block 10 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 53 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.10: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.10: 16.0023 bits
### <a name="blk_11">Block 11 Tensor Group : ~106M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 54 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 55 | blk.11.layer_output_scale.weight | Block 11 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 56 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 57 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 58 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 59 | blk.11.inp_gate.weight | Block 11 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 60 | blk.11.proj.weight | Block 11 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 61 | blk.11.post_attention_norm.weight | Block 11 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 62 | blk.11.post_ffw_norm.weight | Block 11 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 63 | blk.11.post_norm.weight | Block 11 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 64 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 65 | blk.11.attn_k_norm.weight | Block 11 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 66 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
| 67 | blk.11.attn_output.weight | Block 11 Attention Output (W) | ( ~10M) 10485760 | 4096 x 2560 x 1 x 1 | F16 | 16.0000 |
| 68 | blk.11.attn_q_norm.weight | Block 11 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 69 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~10M) 10485760 | 2560 x 4096 x 1 x 1 | F16 | 16.0000 |
| 70 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.11: (~106M) 106182145
- Percentage of total elements: 1.41%
- Bits per Weight (BPW) for blk.11: 16.0021 bits
### <a name="blk_12">Block 12 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 71 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 72 | blk.12.layer_output_scale.weight | Block 12 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 73 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 74 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 75 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 76 | blk.12.inp_gate.weight | Block 12 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 77 | blk.12.proj.weight | Block 12 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 78 | blk.12.post_attention_norm.weight | Block 12 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 79 | blk.12.post_ffw_norm.weight | Block 12 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 80 | blk.12.post_norm.weight | Block 12 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 81 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 82 | blk.12.attn_k_norm.weight | Block 12 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 83 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 84 | blk.12.attn_output.weight | Block 12 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 85 | blk.12.attn_q_norm.weight | Block 12 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 86 | blk.12.attn_q.weight | Block 12 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 87 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.12: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.12: 16.0023 bits
### <a name="blk_13">Block 13 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 88 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 89 | blk.13.layer_output_scale.weight | Block 13 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 90 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 91 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 92 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 93 | blk.13.inp_gate.weight | Block 13 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 94 | blk.13.proj.weight | Block 13 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 95 | blk.13.post_attention_norm.weight | Block 13 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 96 | blk.13.post_ffw_norm.weight | Block 13 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 97 | blk.13.post_norm.weight | Block 13 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 98 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 99 | blk.13.attn_k_norm.weight | Block 13 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 100 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 101 | blk.13.attn_output.weight | Block 13 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 102 | blk.13.attn_q_norm.weight | Block 13 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 103 | blk.13.attn_q.weight | Block 13 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 104 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.13: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.13: 16.0023 bits
### <a name="blk_14">Block 14 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 105 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 106 | blk.14.layer_output_scale.weight | Block 14 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 107 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 108 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 109 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 110 | blk.14.inp_gate.weight | Block 14 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 111 | blk.14.proj.weight | Block 14 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 112 | blk.14.post_attention_norm.weight | Block 14 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 113 | blk.14.post_ffw_norm.weight | Block 14 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 114 | blk.14.post_norm.weight | Block 14 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 115 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 116 | blk.14.attn_k_norm.weight | Block 14 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 117 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 118 | blk.14.attn_output.weight | Block 14 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 119 | blk.14.attn_q_norm.weight | Block 14 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 120 | blk.14.attn_q.weight | Block 14 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 121 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.14: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.14: 16.0023 bits
### <a name="blk_15">Block 15 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 122 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 123 | blk.15.layer_output_scale.weight | Block 15 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 124 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 125 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 126 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 127 | blk.15.inp_gate.weight | Block 15 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 128 | blk.15.proj.weight | Block 15 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 129 | blk.15.post_attention_norm.weight | Block 15 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 130 | blk.15.post_ffw_norm.weight | Block 15 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 131 | blk.15.post_norm.weight | Block 15 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 132 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 133 | blk.15.attn_k_norm.weight | Block 15 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 134 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 135 | blk.15.attn_output.weight | Block 15 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 136 | blk.15.attn_q_norm.weight | Block 15 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 137 | blk.15.attn_q.weight | Block 15 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 138 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.15: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.15: 16.0023 bits
### <a name="blk_16">Block 16 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 139 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 140 | blk.16.layer_output_scale.weight | Block 16 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 141 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 142 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 143 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 144 | blk.16.inp_gate.weight | Block 16 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 145 | blk.16.proj.weight | Block 16 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 146 | blk.16.post_attention_norm.weight | Block 16 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 147 | blk.16.post_ffw_norm.weight | Block 16 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 148 | blk.16.post_norm.weight | Block 16 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 149 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 150 | blk.16.attn_k_norm.weight | Block 16 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 151 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 152 | blk.16.attn_output.weight | Block 16 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 153 | blk.16.attn_q_norm.weight | Block 16 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 154 | blk.16.attn_q.weight | Block 16 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 155 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.16: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.16: 16.0023 bits
### <a name="blk_17">Block 17 Tensor Group : ~106M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 156 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 157 | blk.17.layer_output_scale.weight | Block 17 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 158 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 159 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 160 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 161 | blk.17.inp_gate.weight | Block 17 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 162 | blk.17.proj.weight | Block 17 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 163 | blk.17.post_attention_norm.weight | Block 17 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 164 | blk.17.post_ffw_norm.weight | Block 17 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 165 | blk.17.post_norm.weight | Block 17 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 166 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 167 | blk.17.attn_k_norm.weight | Block 17 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 168 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
| 169 | blk.17.attn_output.weight | Block 17 Attention Output (W) | ( ~10M) 10485760 | 4096 x 2560 x 1 x 1 | F16 | 16.0000 |
| 170 | blk.17.attn_q_norm.weight | Block 17 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 171 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~10M) 10485760 | 2560 x 4096 x 1 x 1 | F16 | 16.0000 |
| 172 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.17: (~106M) 106182145
- Percentage of total elements: 1.41%
- Bits per Weight (BPW) for blk.17: 16.0021 bits
### <a name="blk_18">Block 18 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 173 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 174 | blk.18.layer_output_scale.weight | Block 18 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 175 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 176 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 177 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 178 | blk.18.inp_gate.weight | Block 18 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 179 | blk.18.proj.weight | Block 18 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 180 | blk.18.post_attention_norm.weight | Block 18 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 181 | blk.18.post_ffw_norm.weight | Block 18 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 182 | blk.18.post_norm.weight | Block 18 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 183 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 184 | blk.18.attn_k_norm.weight | Block 18 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 185 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 186 | blk.18.attn_output.weight | Block 18 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 187 | blk.18.attn_q_norm.weight | Block 18 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 188 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 189 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.18: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.18: 16.0023 bits
### <a name="blk_19">Block 19 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 190 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 191 | blk.19.layer_output_scale.weight | Block 19 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 192 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 193 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 194 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 195 | blk.19.inp_gate.weight | Block 19 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 196 | blk.19.proj.weight | Block 19 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 197 | blk.19.post_attention_norm.weight | Block 19 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 198 | blk.19.post_ffw_norm.weight | Block 19 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 199 | blk.19.post_norm.weight | Block 19 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 200 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 201 | blk.19.attn_k_norm.weight | Block 19 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 202 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 203 | blk.19.attn_output.weight | Block 19 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 204 | blk.19.attn_q_norm.weight | Block 19 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 205 | blk.19.attn_q.weight | Block 19 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 206 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.19: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.19: 16.0023 bits
### <a name="blk_2">Block 2 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :------------------------------- | :--------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 207 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 208 | blk.2.layer_output_scale.weight | Block 2 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 209 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 210 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 211 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 212 | blk.2.inp_gate.weight | Block 2 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 213 | blk.2.proj.weight | Block 2 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 214 | blk.2.post_attention_norm.weight | Block 2 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 215 | blk.2.post_ffw_norm.weight | Block 2 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 216 | blk.2.post_norm.weight | Block 2 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 217 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 218 | blk.2.attn_k_norm.weight | Block 2 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 219 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 220 | blk.2.attn_output.weight | Block 2 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 221 | blk.2.attn_q_norm.weight | Block 2 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 222 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 223 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.2: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.2: 16.0023 bits
### <a name="blk_20">Block 20 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 224 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 225 | blk.20.layer_output_scale.weight | Block 20 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 226 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 227 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 228 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 229 | blk.20.inp_gate.weight | Block 20 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 230 | blk.20.proj.weight | Block 20 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 231 | blk.20.post_attention_norm.weight | Block 20 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 232 | blk.20.post_ffw_norm.weight | Block 20 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 233 | blk.20.post_norm.weight | Block 20 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 234 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 235 | blk.20.attn_k_norm.weight | Block 20 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 236 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 237 | blk.20.attn_output.weight | Block 20 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 238 | blk.20.attn_q_norm.weight | Block 20 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 239 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 240 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.20: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.20: 16.0023 bits
### <a name="blk_21">Block 21 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 241 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 242 | blk.21.layer_output_scale.weight | Block 21 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 243 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 244 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 245 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 246 | blk.21.inp_gate.weight | Block 21 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 247 | blk.21.proj.weight | Block 21 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 248 | blk.21.post_attention_norm.weight | Block 21 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 249 | blk.21.post_ffw_norm.weight | Block 21 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 250 | blk.21.post_norm.weight | Block 21 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 251 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 252 | blk.21.attn_k_norm.weight | Block 21 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 253 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 254 | blk.21.attn_output.weight | Block 21 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 255 | blk.21.attn_q_norm.weight | Block 21 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 256 | blk.21.attn_q.weight | Block 21 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 257 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.21: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.21: 16.0023 bits
### <a name="blk_22">Block 22 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 258 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 259 | blk.22.layer_output_scale.weight | Block 22 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 260 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 261 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 262 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 263 | blk.22.inp_gate.weight | Block 22 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 264 | blk.22.proj.weight | Block 22 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 265 | blk.22.post_attention_norm.weight | Block 22 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 266 | blk.22.post_ffw_norm.weight | Block 22 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 267 | blk.22.post_norm.weight | Block 22 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 268 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 269 | blk.22.attn_k_norm.weight | Block 22 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 270 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 271 | blk.22.attn_output.weight | Block 22 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 272 | blk.22.attn_q_norm.weight | Block 22 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 273 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 274 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.22: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.22: 16.0023 bits
### <a name="blk_23">Block 23 Tensor Group : ~106M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 275 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 276 | blk.23.layer_output_scale.weight | Block 23 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 277 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 278 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 279 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 280 | blk.23.inp_gate.weight | Block 23 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 281 | blk.23.proj.weight | Block 23 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 282 | blk.23.post_attention_norm.weight | Block 23 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 283 | blk.23.post_ffw_norm.weight | Block 23 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 284 | blk.23.post_norm.weight | Block 23 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 285 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 286 | blk.23.attn_k_norm.weight | Block 23 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 287 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
| 288 | blk.23.attn_output.weight | Block 23 Attention Output (W) | ( ~10M) 10485760 | 4096 x 2560 x 1 x 1 | F16 | 16.0000 |
| 289 | blk.23.attn_q_norm.weight | Block 23 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 290 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~10M) 10485760 | 2560 x 4096 x 1 x 1 | F16 | 16.0000 |
| 291 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.23: (~106M) 106182145
- Percentage of total elements: 1.41%
- Bits per Weight (BPW) for blk.23: 16.0021 bits
### <a name="blk_24">Block 24 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 292 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 293 | blk.24.layer_output_scale.weight | Block 24 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 294 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 295 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 296 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 297 | blk.24.inp_gate.weight | Block 24 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 298 | blk.24.proj.weight | Block 24 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 299 | blk.24.post_attention_norm.weight | Block 24 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 300 | blk.24.post_ffw_norm.weight | Block 24 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 301 | blk.24.post_norm.weight | Block 24 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 302 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 303 | blk.24.attn_k_norm.weight | Block 24 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 304 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 305 | blk.24.attn_output.weight | Block 24 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 306 | blk.24.attn_q_norm.weight | Block 24 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 307 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 308 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.24: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.24: 16.0023 bits
### <a name="blk_25">Block 25 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 309 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 310 | blk.25.layer_output_scale.weight | Block 25 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 311 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 312 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 313 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 314 | blk.25.inp_gate.weight | Block 25 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 315 | blk.25.proj.weight | Block 25 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 316 | blk.25.post_attention_norm.weight | Block 25 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 317 | blk.25.post_ffw_norm.weight | Block 25 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 318 | blk.25.post_norm.weight | Block 25 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 319 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 320 | blk.25.attn_k_norm.weight | Block 25 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 321 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 322 | blk.25.attn_output.weight | Block 25 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 323 | blk.25.attn_q_norm.weight | Block 25 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 324 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 325 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.25: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.25: 16.0023 bits
### <a name="blk_26">Block 26 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 326 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 327 | blk.26.layer_output_scale.weight | Block 26 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 328 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 329 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 330 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 331 | blk.26.inp_gate.weight | Block 26 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 332 | blk.26.proj.weight | Block 26 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 333 | blk.26.post_attention_norm.weight | Block 26 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 334 | blk.26.post_ffw_norm.weight | Block 26 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 335 | blk.26.post_norm.weight | Block 26 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 336 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 337 | blk.26.attn_k_norm.weight | Block 26 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 338 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 339 | blk.26.attn_output.weight | Block 26 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 340 | blk.26.attn_q_norm.weight | Block 26 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 341 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 342 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.26: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.26: 16.0023 bits
### <a name="blk_27">Block 27 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 343 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 344 | blk.27.layer_output_scale.weight | Block 27 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 345 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 346 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 347 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 348 | blk.27.inp_gate.weight | Block 27 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 349 | blk.27.proj.weight | Block 27 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 350 | blk.27.post_attention_norm.weight | Block 27 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 351 | blk.27.post_ffw_norm.weight | Block 27 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 352 | blk.27.post_norm.weight | Block 27 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 353 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 354 | blk.27.attn_k_norm.weight | Block 27 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 355 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 356 | blk.27.attn_output.weight | Block 27 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 357 | blk.27.attn_q_norm.weight | Block 27 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 358 | blk.27.attn_q.weight | Block 27 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 359 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.27: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.27: 16.0023 bits
### <a name="blk_28">Block 28 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 360 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 361 | blk.28.layer_output_scale.weight | Block 28 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 362 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 363 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 364 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 365 | blk.28.inp_gate.weight | Block 28 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 366 | blk.28.proj.weight | Block 28 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 367 | blk.28.post_attention_norm.weight | Block 28 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 368 | blk.28.post_ffw_norm.weight | Block 28 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 369 | blk.28.post_norm.weight | Block 28 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 370 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 371 | blk.28.attn_k_norm.weight | Block 28 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 372 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 373 | blk.28.attn_output.weight | Block 28 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 374 | blk.28.attn_q_norm.weight | Block 28 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 375 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 376 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.28: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.28: 16.0023 bits
### <a name="blk_29">Block 29 Tensor Group : ~106M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 377 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 378 | blk.29.layer_output_scale.weight | Block 29 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 379 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 380 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 381 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 382 | blk.29.inp_gate.weight | Block 29 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 383 | blk.29.proj.weight | Block 29 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 384 | blk.29.post_attention_norm.weight | Block 29 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 385 | blk.29.post_ffw_norm.weight | Block 29 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 386 | blk.29.post_norm.weight | Block 29 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 387 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 388 | blk.29.attn_k_norm.weight | Block 29 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 389 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
| 390 | blk.29.attn_output.weight | Block 29 Attention Output (W) | ( ~10M) 10485760 | 4096 x 2560 x 1 x 1 | F16 | 16.0000 |
| 391 | blk.29.attn_q_norm.weight | Block 29 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 392 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~10M) 10485760 | 2560 x 4096 x 1 x 1 | F16 | 16.0000 |
| 393 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.29: (~106M) 106182145
- Percentage of total elements: 1.41%
- Bits per Weight (BPW) for blk.29: 16.0021 bits
### <a name="blk_3">Block 3 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :------------------------------- | :--------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 394 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 395 | blk.3.layer_output_scale.weight | Block 3 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 396 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 397 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 398 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 399 | blk.3.inp_gate.weight | Block 3 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 400 | blk.3.proj.weight | Block 3 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 401 | blk.3.post_attention_norm.weight | Block 3 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 402 | blk.3.post_ffw_norm.weight | Block 3 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 403 | blk.3.post_norm.weight | Block 3 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 404 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 405 | blk.3.attn_k_norm.weight | Block 3 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 406 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 407 | blk.3.attn_output.weight | Block 3 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 408 | blk.3.attn_q_norm.weight | Block 3 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 409 | blk.3.attn_q.weight | Block 3 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 410 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.3: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.3: 16.0023 bits
### <a name="blk_30">Block 30 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 411 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 412 | blk.30.layer_output_scale.weight | Block 30 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 413 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 414 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 415 | blk.30.ffn_up.weight | Block 30 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 416 | blk.30.inp_gate.weight | Block 30 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 417 | blk.30.proj.weight | Block 30 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 418 | blk.30.post_attention_norm.weight | Block 30 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 419 | blk.30.post_ffw_norm.weight | Block 30 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 420 | blk.30.post_norm.weight | Block 30 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 421 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 422 | blk.30.attn_k_norm.weight | Block 30 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 423 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 424 | blk.30.attn_output.weight | Block 30 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 425 | blk.30.attn_q_norm.weight | Block 30 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 426 | blk.30.attn_q.weight | Block 30 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 427 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.30: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.30: 16.0023 bits
### <a name="blk_31">Block 31 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 428 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 429 | blk.31.layer_output_scale.weight | Block 31 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 430 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 431 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 432 | blk.31.ffn_up.weight | Block 31 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 433 | blk.31.inp_gate.weight | Block 31 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 434 | blk.31.proj.weight | Block 31 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 435 | blk.31.post_attention_norm.weight | Block 31 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 436 | blk.31.post_ffw_norm.weight | Block 31 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 437 | blk.31.post_norm.weight | Block 31 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 438 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 439 | blk.31.attn_k_norm.weight | Block 31 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 440 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 441 | blk.31.attn_output.weight | Block 31 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 442 | blk.31.attn_q_norm.weight | Block 31 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 443 | blk.31.attn_q.weight | Block 31 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 444 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.31: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.31: 16.0023 bits
### <a name="blk_32">Block 32 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 445 | blk.32.attn_norm.weight | Block 32 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 446 | blk.32.layer_output_scale.weight | Block 32 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 447 | blk.32.ffn_down.weight | Block 32 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 448 | blk.32.ffn_gate.weight | Block 32 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 449 | blk.32.ffn_up.weight | Block 32 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 450 | blk.32.inp_gate.weight | Block 32 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 451 | blk.32.proj.weight | Block 32 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 452 | blk.32.post_attention_norm.weight | Block 32 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 453 | blk.32.post_ffw_norm.weight | Block 32 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 454 | blk.32.post_norm.weight | Block 32 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 455 | blk.32.ffn_norm.weight | Block 32 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 456 | blk.32.attn_k_norm.weight | Block 32 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 457 | blk.32.attn_k.weight | Block 32 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 458 | blk.32.attn_output.weight | Block 32 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 459 | blk.32.attn_q_norm.weight | Block 32 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 460 | blk.32.attn_q.weight | Block 32 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 461 | blk.32.attn_v.weight | Block 32 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.32: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.32: 16.0023 bits
### <a name="blk_33">Block 33 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 462 | blk.33.attn_norm.weight | Block 33 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 463 | blk.33.layer_output_scale.weight | Block 33 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 464 | blk.33.ffn_down.weight | Block 33 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 465 | blk.33.ffn_gate.weight | Block 33 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 466 | blk.33.ffn_up.weight | Block 33 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 467 | blk.33.inp_gate.weight | Block 33 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 468 | blk.33.proj.weight | Block 33 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 469 | blk.33.post_attention_norm.weight | Block 33 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 470 | blk.33.post_ffw_norm.weight | Block 33 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 471 | blk.33.post_norm.weight | Block 33 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 472 | blk.33.ffn_norm.weight | Block 33 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 473 | blk.33.attn_k_norm.weight | Block 33 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 474 | blk.33.attn_k.weight | Block 33 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 475 | blk.33.attn_output.weight | Block 33 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 476 | blk.33.attn_q_norm.weight | Block 33 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 477 | blk.33.attn_q.weight | Block 33 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 478 | blk.33.attn_v.weight | Block 33 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.33: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.33: 16.0023 bits
### <a name="blk_34">Block 34 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 479 | blk.34.attn_norm.weight | Block 34 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 480 | blk.34.layer_output_scale.weight | Block 34 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 481 | blk.34.ffn_down.weight | Block 34 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 482 | blk.34.ffn_gate.weight | Block 34 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 483 | blk.34.ffn_up.weight | Block 34 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 484 | blk.34.inp_gate.weight | Block 34 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 485 | blk.34.proj.weight | Block 34 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 486 | blk.34.post_attention_norm.weight | Block 34 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 487 | blk.34.post_ffw_norm.weight | Block 34 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 488 | blk.34.post_norm.weight | Block 34 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 489 | blk.34.ffn_norm.weight | Block 34 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 490 | blk.34.attn_k_norm.weight | Block 34 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 491 | blk.34.attn_k.weight | Block 34 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 492 | blk.34.attn_output.weight | Block 34 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 493 | blk.34.attn_q_norm.weight | Block 34 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 494 | blk.34.attn_q.weight | Block 34 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 495 | blk.34.attn_v.weight | Block 34 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.34: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.34: 16.0023 bits
### <a name="blk_35">Block 35 Tensor Group : ~106M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 496 | blk.35.attn_norm.weight | Block 35 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 497 | blk.35.layer_output_scale.weight | Block 35 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 498 | blk.35.ffn_down.weight | Block 35 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 499 | blk.35.ffn_gate.weight | Block 35 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 500 | blk.35.ffn_up.weight | Block 35 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 501 | blk.35.inp_gate.weight | Block 35 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 502 | blk.35.proj.weight | Block 35 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 503 | blk.35.post_attention_norm.weight | Block 35 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 504 | blk.35.post_ffw_norm.weight | Block 35 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 505 | blk.35.post_norm.weight | Block 35 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 506 | blk.35.ffn_norm.weight | Block 35 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 507 | blk.35.attn_k_norm.weight | Block 35 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 508 | blk.35.attn_k.weight | Block 35 Attention Key (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
| 509 | blk.35.attn_output.weight | Block 35 Attention Output (W) | ( ~10M) 10485760 | 4096 x 2560 x 1 x 1 | F16 | 16.0000 |
| 510 | blk.35.attn_q_norm.weight | Block 35 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 511 | blk.35.attn_q.weight | Block 35 Attention Query (W) | ( ~10M) 10485760 | 2560 x 4096 x 1 x 1 | F16 | 16.0000 |
| 512 | blk.35.attn_v.weight | Block 35 Attention Value (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.35: (~106M) 106182145
- Percentage of total elements: 1.41%
- Bits per Weight (BPW) for blk.35: 16.0021 bits
### <a name="blk_36">Block 36 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 513 | blk.36.attn_norm.weight | Block 36 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 514 | blk.36.layer_output_scale.weight | Block 36 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 515 | blk.36.ffn_down.weight | Block 36 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 516 | blk.36.ffn_gate.weight | Block 36 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 517 | blk.36.ffn_up.weight | Block 36 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 518 | blk.36.inp_gate.weight | Block 36 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 519 | blk.36.proj.weight | Block 36 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 520 | blk.36.post_attention_norm.weight | Block 36 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 521 | blk.36.post_ffw_norm.weight | Block 36 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 522 | blk.36.post_norm.weight | Block 36 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 523 | blk.36.ffn_norm.weight | Block 36 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 524 | blk.36.attn_k_norm.weight | Block 36 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 525 | blk.36.attn_k.weight | Block 36 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 526 | blk.36.attn_output.weight | Block 36 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 527 | blk.36.attn_q_norm.weight | Block 36 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 528 | blk.36.attn_q.weight | Block 36 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 529 | blk.36.attn_v.weight | Block 36 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.36: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.36: 16.0023 bits
### <a name="blk_37">Block 37 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 530 | blk.37.attn_norm.weight | Block 37 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 531 | blk.37.layer_output_scale.weight | Block 37 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 532 | blk.37.ffn_down.weight | Block 37 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 533 | blk.37.ffn_gate.weight | Block 37 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 534 | blk.37.ffn_up.weight | Block 37 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 535 | blk.37.inp_gate.weight | Block 37 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 536 | blk.37.proj.weight | Block 37 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 537 | blk.37.post_attention_norm.weight | Block 37 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 538 | blk.37.post_ffw_norm.weight | Block 37 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 539 | blk.37.post_norm.weight | Block 37 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 540 | blk.37.ffn_norm.weight | Block 37 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 541 | blk.37.attn_k_norm.weight | Block 37 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 542 | blk.37.attn_k.weight | Block 37 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 543 | blk.37.attn_output.weight | Block 37 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 544 | blk.37.attn_q_norm.weight | Block 37 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 545 | blk.37.attn_q.weight | Block 37 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 546 | blk.37.attn_v.weight | Block 37 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.37: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.37: 16.0023 bits
### <a name="blk_38">Block 38 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 547 | blk.38.attn_norm.weight | Block 38 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 548 | blk.38.layer_output_scale.weight | Block 38 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 549 | blk.38.ffn_down.weight | Block 38 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 550 | blk.38.ffn_gate.weight | Block 38 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 551 | blk.38.ffn_up.weight | Block 38 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 552 | blk.38.inp_gate.weight | Block 38 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 553 | blk.38.proj.weight | Block 38 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 554 | blk.38.post_attention_norm.weight | Block 38 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 555 | blk.38.post_ffw_norm.weight | Block 38 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 556 | blk.38.post_norm.weight | Block 38 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 557 | blk.38.ffn_norm.weight | Block 38 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 558 | blk.38.attn_k_norm.weight | Block 38 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 559 | blk.38.attn_k.weight | Block 38 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 560 | blk.38.attn_output.weight | Block 38 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 561 | blk.38.attn_q_norm.weight | Block 38 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 562 | blk.38.attn_q.weight | Block 38 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 563 | blk.38.attn_v.weight | Block 38 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.38: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.38: 16.0023 bits
### <a name="blk_39">Block 39 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 564 | blk.39.attn_norm.weight | Block 39 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 565 | blk.39.layer_output_scale.weight | Block 39 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 566 | blk.39.ffn_down.weight | Block 39 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 567 | blk.39.ffn_gate.weight | Block 39 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 568 | blk.39.ffn_up.weight | Block 39 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 569 | blk.39.inp_gate.weight | Block 39 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 570 | blk.39.proj.weight | Block 39 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 571 | blk.39.post_attention_norm.weight | Block 39 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 572 | blk.39.post_ffw_norm.weight | Block 39 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 573 | blk.39.post_norm.weight | Block 39 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 574 | blk.39.ffn_norm.weight | Block 39 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 575 | blk.39.attn_k_norm.weight | Block 39 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 576 | blk.39.attn_k.weight | Block 39 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 577 | blk.39.attn_output.weight | Block 39 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 578 | blk.39.attn_q_norm.weight | Block 39 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 579 | blk.39.attn_q.weight | Block 39 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 580 | blk.39.attn_v.weight | Block 39 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.39: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.39: 16.0023 bits
### <a name="blk_4">Block 4 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :------------------------------- | :--------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 581 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 582 | blk.4.layer_output_scale.weight | Block 4 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 583 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 584 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 585 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 586 | blk.4.inp_gate.weight | Block 4 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 587 | blk.4.proj.weight | Block 4 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 588 | blk.4.post_attention_norm.weight | Block 4 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 589 | blk.4.post_ffw_norm.weight | Block 4 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 590 | blk.4.post_norm.weight | Block 4 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 591 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 592 | blk.4.attn_k_norm.weight | Block 4 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 593 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 594 | blk.4.attn_output.weight | Block 4 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 595 | blk.4.attn_q_norm.weight | Block 4 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 596 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 597 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.4: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.4: 16.0023 bits
### <a name="blk_40">Block 40 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 598 | blk.40.attn_norm.weight | Block 40 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 599 | blk.40.layer_output_scale.weight | Block 40 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 600 | blk.40.ffn_down.weight | Block 40 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 601 | blk.40.ffn_gate.weight | Block 40 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 602 | blk.40.ffn_up.weight | Block 40 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 603 | blk.40.inp_gate.weight | Block 40 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 604 | blk.40.proj.weight | Block 40 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 605 | blk.40.post_attention_norm.weight | Block 40 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 606 | blk.40.post_ffw_norm.weight | Block 40 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 607 | blk.40.post_norm.weight | Block 40 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 608 | blk.40.ffn_norm.weight | Block 40 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 609 | blk.40.attn_k_norm.weight | Block 40 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 610 | blk.40.attn_k.weight | Block 40 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 611 | blk.40.attn_output.weight | Block 40 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 612 | blk.40.attn_q_norm.weight | Block 40 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 613 | blk.40.attn_q.weight | Block 40 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 614 | blk.40.attn_v.weight | Block 40 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.40: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.40: 16.0023 bits
### <a name="blk_41">Block 41 Tensor Group : ~106M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :-------------------------------- | :---------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 615 | blk.41.attn_norm.weight | Block 41 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 616 | blk.41.layer_output_scale.weight | Block 41 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 617 | blk.41.ffn_down.weight | Block 41 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 618 | blk.41.ffn_gate.weight | Block 41 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 619 | blk.41.ffn_up.weight | Block 41 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 620 | blk.41.inp_gate.weight | Block 41 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 621 | blk.41.proj.weight | Block 41 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 622 | blk.41.post_attention_norm.weight | Block 41 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 623 | blk.41.post_ffw_norm.weight | Block 41 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 624 | blk.41.post_norm.weight | Block 41 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 625 | blk.41.ffn_norm.weight | Block 41 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 626 | blk.41.attn_k_norm.weight | Block 41 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 627 | blk.41.attn_k.weight | Block 41 Attention Key (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
| 628 | blk.41.attn_output.weight | Block 41 Attention Output (W) | ( ~10M) 10485760 | 4096 x 2560 x 1 x 1 | F16 | 16.0000 |
| 629 | blk.41.attn_q_norm.weight | Block 41 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 630 | blk.41.attn_q.weight | Block 41 Attention Query (W) | ( ~10M) 10485760 | 2560 x 4096 x 1 x 1 | F16 | 16.0000 |
| 631 | blk.41.attn_v.weight | Block 41 Attention Value (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.41: (~106M) 106182145
- Percentage of total elements: 1.41%
- Bits per Weight (BPW) for blk.41: 16.0021 bits
### <a name="blk_5">Block 5 Tensor Group : ~106M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :------------------------------- | :--------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 632 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 633 | blk.5.layer_output_scale.weight | Block 5 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 634 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 635 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 636 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 637 | blk.5.inp_gate.weight | Block 5 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 638 | blk.5.proj.weight | Block 5 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 639 | blk.5.post_attention_norm.weight | Block 5 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 640 | blk.5.post_ffw_norm.weight | Block 5 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 641 | blk.5.post_norm.weight | Block 5 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 642 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 643 | blk.5.attn_k_norm.weight | Block 5 Attn_K_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 644 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
| 645 | blk.5.attn_output.weight | Block 5 Attention Output (W) | ( ~10M) 10485760 | 4096 x 2560 x 1 x 1 | F16 | 16.0000 |
| 646 | blk.5.attn_q_norm.weight | Block 5 Attn_Q_Norm (W) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 | 32.0000 |
| 647 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~10M) 10485760 | 2560 x 4096 x 1 x 1 | F16 | 16.0000 |
| 648 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~3M) 2621440 | 2560 x 1024 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.5: (~106M) 106182145
- Percentage of total elements: 1.41%
- Bits per Weight (BPW) for blk.5: 16.0021 bits
### <a name="blk_6">Block 6 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :------------------------------- | :--------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 649 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 650 | blk.6.layer_output_scale.weight | Block 6 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 651 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 652 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 653 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 654 | blk.6.inp_gate.weight | Block 6 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 655 | blk.6.proj.weight | Block 6 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 656 | blk.6.post_attention_norm.weight | Block 6 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 657 | blk.6.post_ffw_norm.weight | Block 6 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 658 | blk.6.post_norm.weight | Block 6 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 659 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 660 | blk.6.attn_k_norm.weight | Block 6 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 661 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 662 | blk.6.attn_output.weight | Block 6 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 663 | blk.6.attn_q_norm.weight | Block 6 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 664 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 665 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.6: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.6: 16.0023 bits
### <a name="blk_7">Block 7 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :------------------------------- | :--------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 666 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 667 | blk.7.layer_output_scale.weight | Block 7 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 668 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 669 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 670 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 671 | blk.7.inp_gate.weight | Block 7 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 672 | blk.7.proj.weight | Block 7 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 673 | blk.7.post_attention_norm.weight | Block 7 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 674 | blk.7.post_ffw_norm.weight | Block 7 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 675 | blk.7.post_norm.weight | Block 7 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 676 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 677 | blk.7.attn_k_norm.weight | Block 7 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 678 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 679 | blk.7.attn_output.weight | Block 7 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 680 | blk.7.attn_q_norm.weight | Block 7 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 681 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 682 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.7: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.7: 16.0023 bits
### <a name="blk_8">Block 8 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :------------------------------- | :--------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 683 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 684 | blk.8.layer_output_scale.weight | Block 8 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 685 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 686 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 687 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 688 | blk.8.inp_gate.weight | Block 8 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 689 | blk.8.proj.weight | Block 8 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 690 | blk.8.post_attention_norm.weight | Block 8 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 691 | blk.8.post_ffw_norm.weight | Block 8 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 692 | blk.8.post_norm.weight | Block 8 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 693 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 694 | blk.8.attn_k_norm.weight | Block 8 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 695 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 696 | blk.8.attn_output.weight | Block 8 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 697 | blk.8.attn_q_norm.weight | Block 8 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 698 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 699 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.8: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.8: 16.0023 bits
### <a name="blk_9">Block 9 Tensor Group : ~93M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
| ---: | :------------------------------- | :--------------------------------------------- | :--------------- | :-------------------- | :--- | ------: |
| 700 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 701 | blk.9.layer_output_scale.weight | Block 9 Layer_Output_Scale (W) | ( 1) 1 | 1 x 1 x 1 x 1 | F32 | 32.0000 |
| 702 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | ( ~26M) 26214400 | 10240 x 2560 x 1 x 1 | F16 | 16.0000 |
| 703 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 704 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | ( ~26M) 26214400 | 2560 x 10240 x 1 x 1 | F16 | 16.0000 |
| 705 | blk.9.inp_gate.weight | Block 9 Inp_Gate (W) | (~655K) 655360 | 2560 x 256 x 1 x 1 | F16 | 16.0000 |
| 706 | blk.9.proj.weight | Block 9 Proj (W) | (~655K) 655360 | 256 x 2560 x 1 x 1 | F16 | 16.0000 |
| 707 | blk.9.post_attention_norm.weight | Block 9 Post_Attention_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 708 | blk.9.post_ffw_norm.weight | Block 9 Post_Ffw_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 709 | blk.9.post_norm.weight | Block 9 Post_Norm (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 710 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~3K) 2560 | 2560 x 1 x 1 x 1 | F32 | 32.0000 |
| 711 | blk.9.attn_k_norm.weight | Block 9 Attn_K_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 712 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
| 713 | blk.9.attn_output.weight | Block 9 Attention Output (W) | ( ~5M) 5242880 | 2048 x 2560 x 1 x 1 | F16 | 16.0000 |
| 714 | blk.9.attn_q_norm.weight | Block 9 Attn_Q_Norm (W) | ( 256) 256 | 256 x 1 x 1 x 1 | F32 | 32.0000 |
| 715 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~5M) 5242880 | 2560 x 2048 x 1 x 1 | F16 | 16.0000 |
| 716 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~1M) 1310720 | 2560 x 512 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.9: (~93M) 93074433
- Percentage of total elements: 1.24%
- Bits per Weight (BPW) for blk.9: 16.0023 bits
Total BPW for gemma-4-E4B-it-F16.gguf: 16.0012 bits
|