1155 lines
98 KiB
Markdown
1155 lines
98 KiB
Markdown
# Dolphin-Mistral-24B-Venice-Edition-pruned-Q4_K_M.gguf - GGUF Internal File Dump
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- Endian: LITTLE endian
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## Key Value Metadata Store
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There are 46 key-value pairs in this file
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| POS | TYPE | Count | Key | Value |
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|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
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| 1 | UINT32 | 1 | GGUF.version | 3 |
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| 2 | UINT64 | 1 | GGUF.tensor_count | 345 |
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| 3 | UINT64 | 1 | GGUF.kv_count | 43 |
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| 4 | STRING | 1 | general.architecture | `llama` |
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| 5 | STRING | 1 | general.type | `model` |
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| 6 | STRING | 1 | general.name | `Dolphin Mistral 24B Venice Edition` |
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| 7 | STRING | 1 | general.finetune | `Venice-Edition` |
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| 8 | STRING | 1 | general.basename | `Dolphin-Mistral` |
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| 9 | STRING | 1 | general.size_label | `24B` |
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| 10 | STRING | 1 | general.license | `apache-2.0` |
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| 11 | UINT32 | 1 | general.base_model.count | 1 |
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| 12 | STRING | 1 | general.base_model.0.name | `Mistral Small 24B Instruct 2501` |
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| 13 | STRING | 1 | general.base_model.0.version | `2501` |
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| 14 | STRING | 1 | general.base_model.0.organization | `Mistralai` |
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| 15 | STRING | 1 | general.base_model.0.repo_url | `https://huggingface.co/mistral`...`istral-Small-24B-Instruct-2501` |
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| 16 | UINT32 | 1 | llama.context_length | 32768 |
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| 17 | UINT32 | 1 | llama.embedding_length | 5120 |
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| 18 | UINT32 | 1 | llama.feed_forward_length | 32768 |
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| 19 | UINT32 | 1 | llama.attention.head_count | 32 |
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| 20 | UINT32 | 1 | llama.attention.head_count_kv | 8 |
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| 21 | FLOAT32 | 1 | llama.rope.freq_base | 100000000.0 |
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| 22 | FLOAT32 | 1 | llama.attention.layer_norm_rms_epsilon | 1e-05 |
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| 23 | UINT32 | 1 | llama.attention.key_length | 128 |
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| 24 | UINT32 | 1 | llama.attention.value_length | 128 |
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| 25 | UINT32 | 1 | llama.vocab_size | 131072 |
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| 26 | UINT32 | 1 | llama.rope.dimension_count | 128 |
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| 27 | STRING | 1 | tokenizer.ggml.model | `gpt2` |
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| 28 | STRING | 1 | tokenizer.ggml.pre | `tekken` |
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| 29 | [STRING] | 131072 | tokenizer.ggml.tokens | [ `<unk>`, `<s>`, `</s>`, `[INST]`, `[/INST]`, ... ] |
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| 30 | [INT32] | 131072 | tokenizer.ggml.token_type | [ 3, 3, 3, 3, 3, 3, 3, ... ] |
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| 31 | [STRING] | 269443 | tokenizer.ggml.merges | [ `Ġ Ġ`, `Ġ t`, `e r`, `i n`, `Ġ ĠĠĠ`, ... ] |
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| 32 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 1 |
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| 33 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 2 |
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| 34 | UINT32 | 1 | tokenizer.ggml.unknown_token_id | 0 |
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| 35 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 11 |
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| 36 | BOOL | 1 | tokenizer.ggml.add_bos_token | True |
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| 37 | BOOL | 1 | tokenizer.ggml.add_eos_token | False |
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| 38 | STRING | 1 | tokenizer.chat_template | `{%- set today = strftime_now("`...` {%- endif %}{%- endfor %}` |
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| 39 | BOOL | 1 | tokenizer.ggml.add_space_prefix | False |
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| 40 | UINT32 | 1 | general.quantization_version | 2 |
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| 41 | UINT32 | 1 | general.file_type | 15 |
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| 42 | STRING | 1 | quantize.imatrix.file | `./imatrix/imatrix-Dolphin-Mist`...`l-24B-Venice-Edition-small.dat` |
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| 43 | STRING | 1 | quantize.imatrix.dataset | `../../datasets/imatrix/combined_eur_small.txt` |
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| 44 | UINT32 | 1 | quantize.imatrix.entries_count | 281 |
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| 45 | UINT32 | 1 | quantize.imatrix.chunks_count | 3192 |
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| 46 | UINT32 | 1 | llama.block_count | 38 |
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## Tensors Overview ~22B Elements
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Total number of elements in all tensors: 22460892160 Elements
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- [Dolphin-Mistral-24B-Venice-Edition-pruned-Q4\_K\_M.gguf - GGUF Internal File Dump](#Dolphin-Mistral-24B-Venice-Edition-pruned-q4_k_mgguf---gguf-internal-file-dump)
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- [Key Value Metadata Store](#key-value-metadata-store)
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- [Tensors Overview ~22B Elements](#tensors-overview-22b-elements)
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- [Tensor Data Offset](#tensor-data-offset)
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- [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
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- [Block 0 Tensor Group : ~556M Elements](#block-0-tensor-group--556m-elements)
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- [Block 1 Tensor Group : ~556M Elements](#block-1-tensor-group--556m-elements)
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- [Block 2 Tensor Group : ~556M Elements](#block-2-tensor-group--556m-elements)
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- [Block 3 Tensor Group : ~556M Elements](#block-3-tensor-group--556m-elements)
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- [Block 4 Tensor Group : ~556M Elements](#block-4-tensor-group--556m-elements)
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- [Block 5 Tensor Group : ~556M Elements](#block-5-tensor-group--556m-elements)
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- [Block 6 Tensor Group : ~556M Elements](#block-6-tensor-group--556m-elements)
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- [Block 7 Tensor Group : ~556M Elements](#block-7-tensor-group--556m-elements)
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- [Block 8 Tensor Group : ~556M Elements](#block-8-tensor-group--556m-elements)
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- [Block 9 Tensor Group : ~556M Elements](#block-9-tensor-group--556m-elements)
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- [Block 10 Tensor Group : ~556M Elements](#block-10-tensor-group--556m-elements)
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- [Block 11 Tensor Group : ~556M Elements](#block-11-tensor-group--556m-elements)
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- [Block 12 Tensor Group : ~556M Elements](#block-12-tensor-group--556m-elements)
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- [Block 13 Tensor Group : ~556M Elements](#block-13-tensor-group--556m-elements)
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- [Block 14 Tensor Group : ~556M Elements](#block-14-tensor-group--556m-elements)
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- [Block 15 Tensor Group : ~556M Elements](#block-15-tensor-group--556m-elements)
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- [Block 16 Tensor Group : ~556M Elements](#block-16-tensor-group--556m-elements)
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- [Block 17 Tensor Group : ~556M Elements](#block-17-tensor-group--556m-elements)
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- [Block 18 Tensor Group : ~556M Elements](#block-18-tensor-group--556m-elements)
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- [Block 19 Tensor Group : ~556M Elements](#block-19-tensor-group--556m-elements)
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- [Block 20 Tensor Group : ~556M Elements](#block-20-tensor-group--556m-elements)
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- [Block 21 Tensor Group : ~556M Elements](#block-21-tensor-group--556m-elements)
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- [Block 22 Tensor Group : ~556M Elements](#block-22-tensor-group--556m-elements)
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- [Block 23 Tensor Group : ~556M Elements](#block-23-tensor-group--556m-elements)
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- [Block 24 Tensor Group : ~556M Elements](#block-24-tensor-group--556m-elements)
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- [Block 25 Tensor Group : ~556M Elements](#block-25-tensor-group--556m-elements)
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- [Block 26 Tensor Group : ~556M Elements](#block-26-tensor-group--556m-elements)
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- [Block 27 Tensor Group : ~556M Elements](#block-27-tensor-group--556m-elements)
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- [Block 28 Tensor Group : ~556M Elements](#block-28-tensor-group--556m-elements)
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- [Block 29 Tensor Group : ~556M Elements](#block-29-tensor-group--556m-elements)
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- [Block 30 Tensor Group : ~556M Elements](#block-30-tensor-group--556m-elements)
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- [Block 31 Tensor Group : ~556M Elements](#block-31-tensor-group--556m-elements)
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- [Block 32 Tensor Group : ~556M Elements](#block-32-tensor-group--556m-elements)
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- [Block 33 Tensor Group : ~556M Elements](#block-33-tensor-group--556m-elements)
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- [Block 34 Tensor Group : ~556M Elements](#block-34-tensor-group--556m-elements)
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- [Block 35 Tensor Group : ~556M Elements](#block-35-tensor-group--556m-elements)
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- [Block 36 Tensor Group : ~556M Elements](#block-36-tensor-group--556m-elements)
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- [Block 37 Tensor Group : ~556M Elements](#block-37-tensor-group--556m-elements)
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### Tensor Data Offset
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This table contains the offset and data segment relative to start of file
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| T_ID | Tensor Layer Name | Data Offset (B) | Data Size (B) |
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|-----:|:--------------------------|-----------------:|-----------------:|
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| 0 | output.weight | 0x784500 | 0x16800000 |
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| 1 | output_norm.weight | 0x16f84500 | 0x5000 |
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| 2 | token_embd.weight | 0x16f89500 | 0x11300000 |
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| 3 | blk.0.attn_k.weight | 0x28289500 | 0x226000 |
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| 4 | blk.0.attn_norm.weight | 0x284af500 | 0x5000 |
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| 5 | blk.0.attn_output.weight | 0x284b4500 | 0xb40000 |
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| 6 | blk.0.attn_q.weight | 0x28ff4500 | 0x898000 |
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| 7 | blk.0.attn_v.weight | 0x2988c500 | 0x2d0000 |
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| 8 | blk.0.ffn_down.weight | 0x29b5c500 | 0x8340000 |
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| 9 | blk.0.ffn_gate.weight | 0x31e9c500 | 0x44c0000 |
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| 10 | blk.0.ffn_norm.weight | 0x3635c500 | 0x5000 |
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| 11 | blk.0.ffn_up.weight | 0x36361500 | 0x44c0000 |
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| 12 | blk.1.attn_k.weight | 0x3a821500 | 0x226000 |
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| 13 | blk.1.attn_norm.weight | 0x3aa47500 | 0x5000 |
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| 14 | blk.1.attn_output.weight | 0x3aa4c500 | 0xb40000 |
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| 15 | blk.1.attn_q.weight | 0x3b58c500 | 0x898000 |
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| 16 | blk.1.attn_v.weight | 0x3be24500 | 0x2d0000 |
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| 17 | blk.1.ffn_down.weight | 0x3c0f4500 | 0x8340000 |
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| 18 | blk.1.ffn_gate.weight | 0x44434500 | 0x44c0000 |
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| 19 | blk.1.ffn_norm.weight | 0x488f4500 | 0x5000 |
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| 20 | blk.1.ffn_up.weight | 0x488f9500 | 0x44c0000 |
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| 21 | blk.2.attn_k.weight | 0x4cdb9500 | 0x226000 |
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| 22 | blk.2.attn_norm.weight | 0x4cfdf500 | 0x5000 |
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| 23 | blk.2.attn_output.weight | 0x4cfe4500 | 0xb40000 |
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| 24 | blk.2.attn_q.weight | 0x4db24500 | 0x898000 |
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| 25 | blk.2.attn_v.weight | 0x4e3bc500 | 0x2d0000 |
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| 26 | blk.2.ffn_down.weight | 0x4e68c500 | 0x8340000 |
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| 27 | blk.2.ffn_gate.weight | 0x569cc500 | 0x44c0000 |
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| 28 | blk.2.ffn_norm.weight | 0x5ae8c500 | 0x5000 |
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| 29 | blk.2.ffn_up.weight | 0x5ae91500 | 0x44c0000 |
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| 30 | blk.3.attn_k.weight | 0x5f351500 | 0x226000 |
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| 31 | blk.3.attn_norm.weight | 0x5f577500 | 0x5000 |
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| 32 | blk.3.attn_output.weight | 0x5f57c500 | 0xb40000 |
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| 33 | blk.3.attn_q.weight | 0x600bc500 | 0x898000 |
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| 34 | blk.3.attn_v.weight | 0x60954500 | 0x2d0000 |
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| 35 | blk.3.ffn_down.weight | 0x60c24500 | 0x8340000 |
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| 36 | blk.3.ffn_gate.weight | 0x68f64500 | 0x44c0000 |
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| 37 | blk.3.ffn_norm.weight | 0x6d424500 | 0x5000 |
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| 38 | blk.3.ffn_up.weight | 0x6d429500 | 0x44c0000 |
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| 39 | blk.4.attn_k.weight | 0x718e9500 | 0x226000 |
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| 40 | blk.4.attn_norm.weight | 0x71b0f500 | 0x5000 |
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| 41 | blk.4.attn_output.weight | 0x71b14500 | 0xb40000 |
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| 42 | blk.4.attn_q.weight | 0x72654500 | 0x898000 |
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| 43 | blk.4.attn_v.weight | 0x72eec500 | 0x370000 |
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| 44 | blk.4.ffn_down.weight | 0x7325c500 | 0x8340000 |
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| 45 | blk.4.ffn_gate.weight | 0x7b59c500 | 0x44c0000 |
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| 46 | blk.4.ffn_norm.weight | 0x7fa5c500 | 0x5000 |
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| 47 | blk.4.ffn_up.weight | 0x7fa61500 | 0x44c0000 |
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| 48 | blk.5.attn_k.weight | 0x83f21500 | 0x226000 |
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| 49 | blk.5.attn_norm.weight | 0x84147500 | 0x5000 |
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| 50 | blk.5.attn_output.weight | 0x8414c500 | 0xb40000 |
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| 51 | blk.5.attn_q.weight | 0x84c8c500 | 0x898000 |
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| 52 | blk.5.attn_v.weight | 0x85524500 | 0x370000 |
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| 53 | blk.5.ffn_down.weight | 0x85894500 | 0x5a00000 |
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| 54 | blk.5.ffn_gate.weight | 0x8b294500 | 0x44c0000 |
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| 55 | blk.5.ffn_norm.weight | 0x8f754500 | 0x5000 |
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| 56 | blk.5.ffn_up.weight | 0x8f759500 | 0x44c0000 |
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| 57 | blk.6.attn_k.weight | 0x93c19500 | 0x226000 |
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| 58 | blk.6.attn_norm.weight | 0x93e3f500 | 0x5000 |
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| 59 | blk.6.attn_output.weight | 0x93e44500 | 0xb40000 |
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| 60 | blk.6.attn_q.weight | 0x94984500 | 0x898000 |
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| 61 | blk.6.attn_v.weight | 0x9521c500 | 0x2d0000 |
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| 62 | blk.6.ffn_down.weight | 0x954ec500 | 0x5a00000 |
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| 63 | blk.6.ffn_gate.weight | 0x9aeec500 | 0x44c0000 |
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| 64 | blk.6.ffn_norm.weight | 0x9f3ac500 | 0x5000 |
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| 65 | blk.6.ffn_up.weight | 0x9f3b1500 | 0x44c0000 |
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| 66 | blk.7.attn_k.weight | 0xa3871500 | 0x226000 |
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| 67 | blk.7.attn_norm.weight | 0xa3a97500 | 0x5000 |
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| 68 | blk.7.attn_output.weight | 0xa3a9c500 | 0xb40000 |
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| 69 | blk.7.attn_q.weight | 0xa45dc500 | 0x898000 |
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| 70 | blk.7.attn_v.weight | 0xa4e74500 | 0x370000 |
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| 71 | blk.7.ffn_down.weight | 0xa51e4500 | 0x8340000 |
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| 72 | blk.7.ffn_gate.weight | 0xad524500 | 0x44c0000 |
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| 73 | blk.7.ffn_norm.weight | 0xb19e4500 | 0x5000 |
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| 74 | blk.7.ffn_up.weight | 0xb19e9500 | 0x44c0000 |
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| 75 | blk.8.attn_k.weight | 0xb5ea9500 | 0x226000 |
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| 76 | blk.8.attn_norm.weight | 0xb60cf500 | 0x5000 |
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| 77 | blk.8.attn_output.weight | 0xb60d4500 | 0xb40000 |
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| 78 | blk.8.attn_q.weight | 0xb6c14500 | 0x898000 |
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| 79 | blk.8.attn_v.weight | 0xb74ac500 | 0x370000 |
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| 80 | blk.8.ffn_down.weight | 0xb781c500 | 0x5a00000 |
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| 81 | blk.8.ffn_gate.weight | 0xbd21c500 | 0x44c0000 |
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| 82 | blk.8.ffn_norm.weight | 0xc16dc500 | 0x5000 |
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| 83 | blk.8.ffn_up.weight | 0xc16e1500 | 0x44c0000 |
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| 84 | blk.9.attn_k.weight | 0xc5ba1500 | 0x226000 |
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| 85 | blk.9.attn_norm.weight | 0xc5dc7500 | 0x5000 |
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| 86 | blk.9.attn_output.weight | 0xc5dcc500 | 0xb40000 |
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| 87 | blk.9.attn_q.weight | 0xc690c500 | 0x898000 |
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| 88 | blk.9.attn_v.weight | 0xc71a4500 | 0x2d0000 |
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| 89 | blk.9.ffn_down.weight | 0xc7474500 | 0x5a00000 |
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| 90 | blk.9.ffn_gate.weight | 0xcce74500 | 0x44c0000 |
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| 91 | blk.9.ffn_norm.weight | 0xd1334500 | 0x5000 |
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| 92 | blk.9.ffn_up.weight | 0xd1339500 | 0x44c0000 |
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| 93 | blk.10.attn_k.weight | 0xd57f9500 | 0x226000 |
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| 94 | blk.10.attn_norm.weight | 0xd5a1f500 | 0x5000 |
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| 95 | blk.10.attn_output.weight | 0xd5a24500 | 0xb40000 |
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| 96 | blk.10.attn_q.weight | 0xd6564500 | 0x898000 |
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| 97 | blk.10.attn_v.weight | 0xd6dfc500 | 0x370000 |
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| 98 | blk.10.ffn_down.weight | 0xd716c500 | 0x8340000 |
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| 99 | blk.10.ffn_gate.weight | 0xdf4ac500 | 0x44c0000 |
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| 100 | blk.10.ffn_norm.weight | 0xe396c500 | 0x5000 |
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| 101 | blk.10.ffn_up.weight | 0xe3971500 | 0x44c0000 |
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| 102 | blk.11.attn_k.weight | 0xe7e31500 | 0x226000 |
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| 103 | blk.11.attn_norm.weight | 0xe8057500 | 0x5000 |
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| 104 | blk.11.attn_output.weight | 0xe805c500 | 0xb40000 |
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| 105 | blk.11.attn_q.weight | 0xe8b9c500 | 0x898000 |
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| 106 | blk.11.attn_v.weight | 0xe9434500 | 0x370000 |
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| 107 | blk.11.ffn_down.weight | 0xe97a4500 | 0x5a00000 |
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| 108 | blk.11.ffn_gate.weight | 0xef1a4500 | 0x44c0000 |
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| 109 | blk.11.ffn_norm.weight | 0xf3664500 | 0x5000 |
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| 110 | blk.11.ffn_up.weight | 0xf3669500 | 0x44c0000 |
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| 111 | blk.12.attn_k.weight | 0xf7b29500 | 0x226000 |
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| 112 | blk.12.attn_norm.weight | 0xf7d4f500 | 0x5000 |
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| 113 | blk.12.attn_output.weight | 0xf7d54500 | 0xb40000 |
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| 114 | blk.12.attn_q.weight | 0xf8894500 | 0x898000 |
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| 115 | blk.12.attn_v.weight | 0xf912c500 | 0x2d0000 |
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| 116 | blk.12.ffn_down.weight | 0xf93fc500 | 0x5a00000 |
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| 117 | blk.12.ffn_gate.weight | 0xfedfc500 | 0x44c0000 |
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| 118 | blk.12.ffn_norm.weight | 0x1032bc500 | 0x5000 |
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| 119 | blk.12.ffn_up.weight | 0x1032c1500 | 0x44c0000 |
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| 120 | blk.13.attn_k.weight | 0x107781500 | 0x226000 |
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| 121 | blk.13.attn_norm.weight | 0x1079a7500 | 0x5000 |
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| 122 | blk.13.attn_output.weight | 0x1079ac500 | 0xb40000 |
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| 123 | blk.13.attn_q.weight | 0x1084ec500 | 0x898000 |
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| 124 | blk.13.attn_v.weight | 0x108d84500 | 0x370000 |
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| 125 | blk.13.ffn_down.weight | 0x1090f4500 | 0x8340000 |
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| 126 | blk.13.ffn_gate.weight | 0x111434500 | 0x44c0000 |
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| 127 | blk.13.ffn_norm.weight | 0x1158f4500 | 0x5000 |
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| 128 | blk.13.ffn_up.weight | 0x1158f9500 | 0x44c0000 |
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| 129 | blk.14.attn_k.weight | 0x119db9500 | 0x226000 |
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| 130 | blk.14.attn_norm.weight | 0x119fdf500 | 0x5000 |
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| 131 | blk.14.attn_output.weight | 0x119fe4500 | 0xb40000 |
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| 132 | blk.14.attn_q.weight | 0x11ab24500 | 0x898000 |
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| 133 | blk.14.attn_v.weight | 0x11b3bc500 | 0x370000 |
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| 134 | blk.14.ffn_down.weight | 0x11b72c500 | 0x5a00000 |
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| 135 | blk.14.ffn_gate.weight | 0x12112c500 | 0x44c0000 |
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| 136 | blk.14.ffn_norm.weight | 0x1255ec500 | 0x5000 |
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| 137 | blk.14.ffn_up.weight | 0x1255f1500 | 0x44c0000 |
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| 138 | blk.15.attn_k.weight | 0x129ab1500 | 0x226000 |
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| 139 | blk.15.attn_norm.weight | 0x129cd7500 | 0x5000 |
|
|
| 140 | blk.15.attn_output.weight | 0x129cdc500 | 0xb40000 |
|
|
| 141 | blk.15.attn_q.weight | 0x12a81c500 | 0x898000 |
|
|
| 142 | blk.15.attn_v.weight | 0x12b0b4500 | 0x2d0000 |
|
|
| 143 | blk.15.ffn_down.weight | 0x12b384500 | 0x5a00000 |
|
|
| 144 | blk.15.ffn_gate.weight | 0x130d84500 | 0x44c0000 |
|
|
| 145 | blk.15.ffn_norm.weight | 0x135244500 | 0x5000 |
|
|
| 146 | blk.15.ffn_up.weight | 0x135249500 | 0x44c0000 |
|
|
| 147 | blk.16.attn_k.weight | 0x139709500 | 0x226000 |
|
|
| 148 | blk.16.attn_norm.weight | 0x13992f500 | 0x5000 |
|
|
| 149 | blk.16.attn_output.weight | 0x139934500 | 0xb40000 |
|
|
| 150 | blk.16.attn_q.weight | 0x13a474500 | 0x898000 |
|
|
| 151 | blk.16.attn_v.weight | 0x13ad0c500 | 0x370000 |
|
|
| 152 | blk.16.ffn_down.weight | 0x13b07c500 | 0x8340000 |
|
|
| 153 | blk.16.ffn_gate.weight | 0x1433bc500 | 0x44c0000 |
|
|
| 154 | blk.16.ffn_norm.weight | 0x14787c500 | 0x5000 |
|
|
| 155 | blk.16.ffn_up.weight | 0x147881500 | 0x44c0000 |
|
|
| 156 | blk.17.attn_k.weight | 0x14bd41500 | 0x2d0000 |
|
|
| 157 | blk.17.attn_norm.weight | 0x14c011500 | 0x5000 |
|
|
| 158 | blk.17.attn_output.weight | 0x14c016500 | 0xb40000 |
|
|
| 159 | blk.17.attn_q.weight | 0x14cb56500 | 0xb40000 |
|
|
| 160 | blk.17.attn_v.weight | 0x14d696500 | 0x370000 |
|
|
| 161 | blk.17.ffn_down.weight | 0x14da06500 | 0x5a00000 |
|
|
| 162 | blk.17.ffn_gate.weight | 0x153406500 | 0x44c0000 |
|
|
| 163 | blk.17.ffn_norm.weight | 0x1578c6500 | 0x5000 |
|
|
| 164 | blk.17.ffn_up.weight | 0x1578cb500 | 0x44c0000 |
|
|
| 165 | blk.18.attn_k.weight | 0x15bd8b500 | 0x2d0000 |
|
|
| 166 | blk.18.attn_norm.weight | 0x15c05b500 | 0x5000 |
|
|
| 167 | blk.18.attn_output.weight | 0x15c060500 | 0xb40000 |
|
|
| 168 | blk.18.attn_q.weight | 0x15cba0500 | 0xb40000 |
|
|
| 169 | blk.18.attn_v.weight | 0x15d6e0500 | 0x370000 |
|
|
| 170 | blk.18.ffn_down.weight | 0x15da50500 | 0x5a00000 |
|
|
| 171 | blk.18.ffn_gate.weight | 0x163450500 | 0x44c0000 |
|
|
| 172 | blk.18.ffn_norm.weight | 0x167910500 | 0x5000 |
|
|
| 173 | blk.18.ffn_up.weight | 0x167915500 | 0x44c0000 |
|
|
| 174 | blk.19.attn_k.weight | 0x16bdd5500 | 0x226000 |
|
|
| 175 | blk.19.attn_norm.weight | 0x16bffb500 | 0x5000 |
|
|
| 176 | blk.19.attn_output.weight | 0x16c000500 | 0xb40000 |
|
|
| 177 | blk.19.attn_q.weight | 0x16cb40500 | 0x898000 |
|
|
| 178 | blk.19.attn_v.weight | 0x16d3d8500 | 0x370000 |
|
|
| 179 | blk.19.ffn_down.weight | 0x16d748500 | 0x8340000 |
|
|
| 180 | blk.19.ffn_gate.weight | 0x175a88500 | 0x44c0000 |
|
|
| 181 | blk.19.ffn_norm.weight | 0x179f48500 | 0x5000 |
|
|
| 182 | blk.19.ffn_up.weight | 0x179f4d500 | 0x44c0000 |
|
|
| 183 | blk.20.attn_k.weight | 0x17e40d500 | 0x2d0000 |
|
|
| 184 | blk.20.attn_norm.weight | 0x17e6dd500 | 0x5000 |
|
|
| 185 | blk.20.attn_output.weight | 0x17e6e2500 | 0xb40000 |
|
|
| 186 | blk.20.attn_q.weight | 0x17f222500 | 0xb40000 |
|
|
| 187 | blk.20.attn_v.weight | 0x17fd62500 | 0x370000 |
|
|
| 188 | blk.20.ffn_down.weight | 0x1800d2500 | 0x5a00000 |
|
|
| 189 | blk.20.ffn_gate.weight | 0x185ad2500 | 0x5a00000 |
|
|
| 190 | blk.20.ffn_norm.weight | 0x18b4d2500 | 0x5000 |
|
|
| 191 | blk.20.ffn_up.weight | 0x18b4d7500 | 0x5a00000 |
|
|
| 192 | blk.21.attn_k.weight | 0x190ed7500 | 0x226000 |
|
|
| 193 | blk.21.attn_norm.weight | 0x1910fd500 | 0x5000 |
|
|
| 194 | blk.21.attn_output.weight | 0x191102500 | 0xb40000 |
|
|
| 195 | blk.21.attn_q.weight | 0x191c42500 | 0x898000 |
|
|
| 196 | blk.21.attn_v.weight | 0x1924da500 | 0x2d0000 |
|
|
| 197 | blk.21.ffn_down.weight | 0x1927aa500 | 0x5a00000 |
|
|
| 198 | blk.21.ffn_gate.weight | 0x1981aa500 | 0x5a00000 |
|
|
| 199 | blk.21.ffn_norm.weight | 0x19dbaa500 | 0x5000 |
|
|
| 200 | blk.21.ffn_up.weight | 0x19dbaf500 | 0x5a00000 |
|
|
| 201 | blk.22.attn_k.weight | 0x1a35af500 | 0x2d0000 |
|
|
| 202 | blk.22.attn_norm.weight | 0x1a387f500 | 0x5000 |
|
|
| 203 | blk.22.attn_output.weight | 0x1a3884500 | 0xb40000 |
|
|
| 204 | blk.22.attn_q.weight | 0x1a43c4500 | 0xb40000 |
|
|
| 205 | blk.22.attn_v.weight | 0x1a4f04500 | 0x370000 |
|
|
| 206 | blk.22.ffn_down.weight | 0x1a5274500 | 0x8340000 |
|
|
| 207 | blk.22.ffn_gate.weight | 0x1ad5b4500 | 0x5a00000 |
|
|
| 208 | blk.22.ffn_norm.weight | 0x1b2fb4500 | 0x5000 |
|
|
| 209 | blk.22.ffn_up.weight | 0x1b2fb9500 | 0x5a00000 |
|
|
| 210 | blk.23.attn_k.weight | 0x1b89b9500 | 0x2d0000 |
|
|
| 211 | blk.23.attn_norm.weight | 0x1b8c89500 | 0x5000 |
|
|
| 212 | blk.23.attn_output.weight | 0x1b8c8e500 | 0xb40000 |
|
|
| 213 | blk.23.attn_q.weight | 0x1b97ce500 | 0xb40000 |
|
|
| 214 | blk.23.attn_v.weight | 0x1ba30e500 | 0x370000 |
|
|
| 215 | blk.23.ffn_down.weight | 0x1ba67e500 | 0x5a00000 |
|
|
| 216 | blk.23.ffn_gate.weight | 0x1c007e500 | 0x5a00000 |
|
|
| 217 | blk.23.ffn_norm.weight | 0x1c5a7e500 | 0x5000 |
|
|
| 218 | blk.23.ffn_up.weight | 0x1c5a83500 | 0x5a00000 |
|
|
| 219 | blk.24.attn_k.weight | 0x1cb483500 | 0x2d0000 |
|
|
| 220 | blk.24.attn_norm.weight | 0x1cb753500 | 0x5000 |
|
|
| 221 | blk.24.attn_output.weight | 0x1cb758500 | 0xb40000 |
|
|
| 222 | blk.24.attn_q.weight | 0x1cc298500 | 0xb40000 |
|
|
| 223 | blk.24.attn_v.weight | 0x1ccdd8500 | 0x370000 |
|
|
| 224 | blk.24.ffn_down.weight | 0x1cd148500 | 0x5a00000 |
|
|
| 225 | blk.24.ffn_gate.weight | 0x1d2b48500 | 0x5a00000 |
|
|
| 226 | blk.24.ffn_norm.weight | 0x1d8548500 | 0x5000 |
|
|
| 227 | blk.24.ffn_up.weight | 0x1d854d500 | 0x5a00000 |
|
|
| 228 | blk.25.attn_k.weight | 0x1ddf4d500 | 0x2d0000 |
|
|
| 229 | blk.25.attn_norm.weight | 0x1de21d500 | 0x5000 |
|
|
| 230 | blk.25.attn_output.weight | 0x1de222500 | 0xb40000 |
|
|
| 231 | blk.25.attn_q.weight | 0x1ded62500 | 0xb40000 |
|
|
| 232 | blk.25.attn_v.weight | 0x1df8a2500 | 0x370000 |
|
|
| 233 | blk.25.ffn_down.weight | 0x1dfc12500 | 0x8340000 |
|
|
| 234 | blk.25.ffn_gate.weight | 0x1e7f52500 | 0x5a00000 |
|
|
| 235 | blk.25.ffn_norm.weight | 0x1ed952500 | 0x5000 |
|
|
| 236 | blk.25.ffn_up.weight | 0x1ed957500 | 0x5a00000 |
|
|
| 237 | blk.26.attn_k.weight | 0x1f3357500 | 0x2d0000 |
|
|
| 238 | blk.26.attn_norm.weight | 0x1f3627500 | 0x5000 |
|
|
| 239 | blk.26.attn_output.weight | 0x1f362c500 | 0xb40000 |
|
|
| 240 | blk.26.attn_q.weight | 0x1f416c500 | 0xb40000 |
|
|
| 241 | blk.26.attn_v.weight | 0x1f4cac500 | 0x370000 |
|
|
| 242 | blk.26.ffn_down.weight | 0x1f501c500 | 0x5a00000 |
|
|
| 243 | blk.26.ffn_gate.weight | 0x1faa1c500 | 0x5a00000 |
|
|
| 244 | blk.26.ffn_norm.weight | 0x20041c500 | 0x5000 |
|
|
| 245 | blk.26.ffn_up.weight | 0x200421500 | 0x5a00000 |
|
|
| 246 | blk.27.attn_k.weight | 0x205e21500 | 0x226000 |
|
|
| 247 | blk.27.attn_norm.weight | 0x206047500 | 0x5000 |
|
|
| 248 | blk.27.attn_output.weight | 0x20604c500 | 0xb40000 |
|
|
| 249 | blk.27.attn_q.weight | 0x206b8c500 | 0x898000 |
|
|
| 250 | blk.27.attn_v.weight | 0x207424500 | 0x2d0000 |
|
|
| 251 | blk.27.ffn_down.weight | 0x2076f4500 | 0x5a00000 |
|
|
| 252 | blk.27.ffn_gate.weight | 0x20d0f4500 | 0x5a00000 |
|
|
| 253 | blk.27.ffn_norm.weight | 0x212af4500 | 0x5000 |
|
|
| 254 | blk.27.ffn_up.weight | 0x212af9500 | 0x5a00000 |
|
|
| 255 | blk.28.attn_k.weight | 0x2184f9500 | 0x2d0000 |
|
|
| 256 | blk.28.attn_norm.weight | 0x2187c9500 | 0x5000 |
|
|
| 257 | blk.28.attn_output.weight | 0x2187ce500 | 0xb40000 |
|
|
| 258 | blk.28.attn_q.weight | 0x21930e500 | 0xb40000 |
|
|
| 259 | blk.28.attn_v.weight | 0x219e4e500 | 0x370000 |
|
|
| 260 | blk.28.ffn_down.weight | 0x21a1be500 | 0x8340000 |
|
|
| 261 | blk.28.ffn_gate.weight | 0x2224fe500 | 0x5a00000 |
|
|
| 262 | blk.28.ffn_norm.weight | 0x227efe500 | 0x5000 |
|
|
| 263 | blk.28.ffn_up.weight | 0x227f03500 | 0x5a00000 |
|
|
| 264 | blk.29.attn_k.weight | 0x22d903500 | 0x2d0000 |
|
|
| 265 | blk.29.attn_norm.weight | 0x22dbd3500 | 0x5000 |
|
|
| 266 | blk.29.attn_output.weight | 0x22dbd8500 | 0xb40000 |
|
|
| 267 | blk.29.attn_q.weight | 0x22e718500 | 0xb40000 |
|
|
| 268 | blk.29.attn_v.weight | 0x22f258500 | 0x370000 |
|
|
| 269 | blk.29.ffn_down.weight | 0x22f5c8500 | 0x5a00000 |
|
|
| 270 | blk.29.ffn_gate.weight | 0x234fc8500 | 0x5a00000 |
|
|
| 271 | blk.29.ffn_norm.weight | 0x23a9c8500 | 0x5000 |
|
|
| 272 | blk.29.ffn_up.weight | 0x23a9cd500 | 0x5a00000 |
|
|
| 273 | blk.30.attn_k.weight | 0x2403cd500 | 0x2d0000 |
|
|
| 274 | blk.30.attn_norm.weight | 0x24069d500 | 0x5000 |
|
|
| 275 | blk.30.attn_output.weight | 0x2406a2500 | 0xb40000 |
|
|
| 276 | blk.30.attn_q.weight | 0x2411e2500 | 0xb40000 |
|
|
| 277 | blk.30.attn_v.weight | 0x241d22500 | 0x370000 |
|
|
| 278 | blk.30.ffn_down.weight | 0x242092500 | 0x5a00000 |
|
|
| 279 | blk.30.ffn_gate.weight | 0x247a92500 | 0x5a00000 |
|
|
| 280 | blk.30.ffn_norm.weight | 0x24d492500 | 0x5000 |
|
|
| 281 | blk.30.ffn_up.weight | 0x24d497500 | 0x5a00000 |
|
|
| 282 | blk.31.attn_k.weight | 0x252e97500 | 0x2d0000 |
|
|
| 283 | blk.31.attn_norm.weight | 0x253167500 | 0x5000 |
|
|
| 284 | blk.31.attn_output.weight | 0x25316c500 | 0xb40000 |
|
|
| 285 | blk.31.attn_q.weight | 0x253cac500 | 0xb40000 |
|
|
| 286 | blk.31.attn_v.weight | 0x2547ec500 | 0x370000 |
|
|
| 287 | blk.31.ffn_down.weight | 0x254b5c500 | 0x8340000 |
|
|
| 288 | blk.31.ffn_gate.weight | 0x25ce9c500 | 0x5a00000 |
|
|
| 289 | blk.31.ffn_norm.weight | 0x26289c500 | 0x5000 |
|
|
| 290 | blk.31.ffn_up.weight | 0x2628a1500 | 0x5a00000 |
|
|
| 291 | blk.32.attn_k.weight | 0x2682a1500 | 0x2d0000 |
|
|
| 292 | blk.32.attn_norm.weight | 0x268571500 | 0x5000 |
|
|
| 293 | blk.32.attn_output.weight | 0x268576500 | 0xb40000 |
|
|
| 294 | blk.32.attn_q.weight | 0x2690b6500 | 0xb40000 |
|
|
| 295 | blk.32.attn_v.weight | 0x269bf6500 | 0x370000 |
|
|
| 296 | blk.32.ffn_down.weight | 0x269f66500 | 0x5a00000 |
|
|
| 297 | blk.32.ffn_gate.weight | 0x26f966500 | 0x5a00000 |
|
|
| 298 | blk.32.ffn_norm.weight | 0x275366500 | 0x5000 |
|
|
| 299 | blk.32.ffn_up.weight | 0x27536b500 | 0x5a00000 |
|
|
| 300 | blk.33.attn_k.weight | 0x27ad6b500 | 0x2d0000 |
|
|
| 301 | blk.33.attn_norm.weight | 0x27b03b500 | 0x5000 |
|
|
| 302 | blk.33.attn_output.weight | 0x27b040500 | 0xb40000 |
|
|
| 303 | blk.33.attn_q.weight | 0x27bb80500 | 0xb40000 |
|
|
| 304 | blk.33.attn_v.weight | 0x27c6c0500 | 0x370000 |
|
|
| 305 | blk.33.ffn_down.weight | 0x27ca30500 | 0x5a00000 |
|
|
| 306 | blk.33.ffn_gate.weight | 0x282430500 | 0x5a00000 |
|
|
| 307 | blk.33.ffn_norm.weight | 0x287e30500 | 0x5000 |
|
|
| 308 | blk.33.ffn_up.weight | 0x287e35500 | 0x5a00000 |
|
|
| 309 | blk.34.attn_k.weight | 0x28d835500 | 0x2d0000 |
|
|
| 310 | blk.34.attn_norm.weight | 0x28db05500 | 0x5000 |
|
|
| 311 | blk.34.attn_output.weight | 0x28db0a500 | 0xb40000 |
|
|
| 312 | blk.34.attn_q.weight | 0x28e64a500 | 0xb40000 |
|
|
| 313 | blk.34.attn_v.weight | 0x28f18a500 | 0x370000 |
|
|
| 314 | blk.34.ffn_down.weight | 0x28f4fa500 | 0x8340000 |
|
|
| 315 | blk.34.ffn_gate.weight | 0x29783a500 | 0x5a00000 |
|
|
| 316 | blk.34.ffn_norm.weight | 0x29d23a500 | 0x5000 |
|
|
| 317 | blk.34.ffn_up.weight | 0x29d23f500 | 0x5a00000 |
|
|
| 318 | blk.35.attn_k.weight | 0x2a2c3f500 | 0x2d0000 |
|
|
| 319 | blk.35.attn_norm.weight | 0x2a2f0f500 | 0x5000 |
|
|
| 320 | blk.35.attn_output.weight | 0x2a2f14500 | 0xb40000 |
|
|
| 321 | blk.35.attn_q.weight | 0x2a3a54500 | 0xb40000 |
|
|
| 322 | blk.35.attn_v.weight | 0x2a4594500 | 0x370000 |
|
|
| 323 | blk.35.ffn_down.weight | 0x2a4904500 | 0x8340000 |
|
|
| 324 | blk.35.ffn_gate.weight | 0x2acc44500 | 0x5a00000 |
|
|
| 325 | blk.35.ffn_norm.weight | 0x2b2644500 | 0x5000 |
|
|
| 326 | blk.35.ffn_up.weight | 0x2b2649500 | 0x5a00000 |
|
|
| 327 | blk.36.attn_k.weight | 0x2b8049500 | 0x2d0000 |
|
|
| 328 | blk.36.attn_norm.weight | 0x2b8319500 | 0x5000 |
|
|
| 329 | blk.36.attn_output.weight | 0x2b831e500 | 0xb40000 |
|
|
| 330 | blk.36.attn_q.weight | 0x2b8e5e500 | 0xb40000 |
|
|
| 331 | blk.36.attn_v.weight | 0x2b999e500 | 0x370000 |
|
|
| 332 | blk.36.ffn_down.weight | 0x2b9d0e500 | 0x8340000 |
|
|
| 333 | blk.36.ffn_gate.weight | 0x2c204e500 | 0x5a00000 |
|
|
| 334 | blk.36.ffn_norm.weight | 0x2c7a4e500 | 0x5000 |
|
|
| 335 | blk.36.ffn_up.weight | 0x2c7a53500 | 0x5a00000 |
|
|
| 336 | blk.37.attn_k.weight | 0x2cd453500 | 0x2d0000 |
|
|
| 337 | blk.37.attn_norm.weight | 0x2cd723500 | 0x5000 |
|
|
| 338 | blk.37.attn_output.weight | 0x2cd728500 | 0xb40000 |
|
|
| 339 | blk.37.attn_q.weight | 0x2ce268500 | 0xb40000 |
|
|
| 340 | blk.37.attn_v.weight | 0x2ceda8500 | 0x370000 |
|
|
| 341 | blk.37.ffn_down.weight | 0x2cf118500 | 0x8340000 |
|
|
| 342 | blk.37.ffn_gate.weight | 0x2d7458500 | 0x5a00000 |
|
|
| 343 | blk.37.ffn_norm.weight | 0x2dce58500 | 0x5000 |
|
|
| 344 | blk.37.ffn_up.weight | 0x2dce5d500 | 0x5a00000 |
|
|
|
|
### <a name="base">Base Tensor Group : ~1B Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
|
|
| 0 | output.weight | Output (W) | (~671M) 671088640 | 5120 x 131072 x 1 x 1 | Q4_K |
|
|
| 1 | output_norm.weight | Output Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 2 | token_embd.weight | Token Embedding (W) | (~671M) 671088640 | 5120 x 131072 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in base: ( ~1B) 1342182400
|
|
- Percentage of total elements: 5.98%
|
|
|
|
|
|
### <a name="blk_0">Block 0 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 3 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 4 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 5 | blk.0.attn_output.weight | Block 0 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 6 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 7 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 8 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 9 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 10 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 11 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.0: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_1">Block 1 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 12 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 13 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 14 | blk.1.attn_output.weight | Block 1 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 15 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 16 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 17 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 18 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 19 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 20 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.1: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_2">Block 2 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 21 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 22 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 23 | blk.2.attn_output.weight | Block 2 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 24 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 25 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 26 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 27 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 28 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 29 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.2: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_3">Block 3 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 30 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 31 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 32 | blk.3.attn_output.weight | Block 3 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 33 | blk.3.attn_q.weight | Block 3 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 34 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 35 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 36 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 37 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 38 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.3: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_4">Block 4 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 39 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 40 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 41 | blk.4.attn_output.weight | Block 4 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 42 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 43 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 44 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 45 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 46 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 47 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.4: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_5">Block 5 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 48 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 49 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 50 | blk.5.attn_output.weight | Block 5 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 51 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 52 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 53 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 54 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 55 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 56 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.5: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_6">Block 6 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 57 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 58 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 59 | blk.6.attn_output.weight | Block 6 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 60 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 61 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 62 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 63 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 64 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 65 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.6: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_7">Block 7 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 66 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 67 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 68 | blk.7.attn_output.weight | Block 7 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 69 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 70 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 71 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 72 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 73 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 74 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.7: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_8">Block 8 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 75 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 76 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 77 | blk.8.attn_output.weight | Block 8 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 78 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 79 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 80 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 81 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 82 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 83 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.8: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_9">Block 9 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 84 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 85 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 86 | blk.9.attn_output.weight | Block 9 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 87 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 88 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 89 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 90 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 91 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 92 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.9: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_10">Block 10 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 93 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 94 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 95 | blk.10.attn_output.weight | Block 10 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 96 | blk.10.attn_q.weight | Block 10 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 97 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 98 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 99 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 100 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 101 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.10: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_11">Block 11 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 102 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 103 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 104 | blk.11.attn_output.weight | Block 11 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 105 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 106 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 107 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 108 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 109 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 110 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.11: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_12">Block 12 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 111 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 112 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 113 | blk.12.attn_output.weight | Block 12 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 114 | blk.12.attn_q.weight | Block 12 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 115 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 116 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 117 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 118 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 119 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.12: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_13">Block 13 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 120 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 121 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 122 | blk.13.attn_output.weight | Block 13 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 123 | blk.13.attn_q.weight | Block 13 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 124 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 125 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 126 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 127 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 128 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.13: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_14">Block 14 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 129 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 130 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 131 | blk.14.attn_output.weight | Block 14 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 132 | blk.14.attn_q.weight | Block 14 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 133 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 134 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 135 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 136 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 137 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.14: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_15">Block 15 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 138 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 139 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 140 | blk.15.attn_output.weight | Block 15 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 141 | blk.15.attn_q.weight | Block 15 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 142 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 143 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 144 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 145 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 146 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.15: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_16">Block 16 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 147 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 148 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 149 | blk.16.attn_output.weight | Block 16 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 150 | blk.16.attn_q.weight | Block 16 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 151 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 152 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 153 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 154 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 155 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.16: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_17">Block 17 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 156 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 157 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 158 | blk.17.attn_output.weight | Block 17 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 159 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 160 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 161 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 162 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 163 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 164 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.17: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_18">Block 18 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 165 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 166 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 167 | blk.18.attn_output.weight | Block 18 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 168 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 169 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 170 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 171 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 172 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 173 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.18: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_19">Block 19 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 174 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 175 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 176 | blk.19.attn_output.weight | Block 19 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 177 | blk.19.attn_q.weight | Block 19 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 178 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 179 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 180 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
| 181 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 182 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K |
|
|
|
|
- Total elements in blk.19: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_20">Block 20 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 183 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 184 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 185 | blk.20.attn_output.weight | Block 20 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 186 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 187 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 188 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 189 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 190 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 191 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.20: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_21">Block 21 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 192 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 193 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 194 | blk.21.attn_output.weight | Block 21 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 195 | blk.21.attn_q.weight | Block 21 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 196 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 197 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 198 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 199 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 200 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.21: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_22">Block 22 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 201 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 202 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 203 | blk.22.attn_output.weight | Block 22 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 204 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 205 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 206 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 207 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 208 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 209 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.22: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_23">Block 23 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 210 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 211 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 212 | blk.23.attn_output.weight | Block 23 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 213 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 214 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 215 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 216 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 217 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 218 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.23: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_24">Block 24 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 219 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 220 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 221 | blk.24.attn_output.weight | Block 24 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 222 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 223 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 224 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 225 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 226 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 227 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.24: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_25">Block 25 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 228 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 229 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 230 | blk.25.attn_output.weight | Block 25 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 231 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 232 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 233 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 234 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 235 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 236 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.25: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_26">Block 26 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 237 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 238 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 239 | blk.26.attn_output.weight | Block 26 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 240 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 241 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 242 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 243 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 244 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 245 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.26: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_27">Block 27 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 246 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 247 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 248 | blk.27.attn_output.weight | Block 27 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 249 | blk.27.attn_q.weight | Block 27 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K |
|
|
| 250 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 251 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 252 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 253 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 254 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.27: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_28">Block 28 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 255 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 256 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 257 | blk.28.attn_output.weight | Block 28 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 258 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 259 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 260 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 261 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 262 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 263 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.28: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_29">Block 29 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 264 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 265 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 266 | blk.29.attn_output.weight | Block 29 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 267 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 268 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 269 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 270 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 271 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 272 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.29: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_30">Block 30 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 273 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 274 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 275 | blk.30.attn_output.weight | Block 30 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 276 | blk.30.attn_q.weight | Block 30 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 277 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 278 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 279 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 280 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 281 | blk.30.ffn_up.weight | Block 30 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.30: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_31">Block 31 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 282 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 283 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 284 | blk.31.attn_output.weight | Block 31 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 285 | blk.31.attn_q.weight | Block 31 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 286 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 287 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 288 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 289 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 290 | blk.31.ffn_up.weight | Block 31 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.31: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_32">Block 32 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 291 | blk.32.attn_k.weight | Block 32 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 292 | blk.32.attn_norm.weight | Block 32 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 293 | blk.32.attn_output.weight | Block 32 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 294 | blk.32.attn_q.weight | Block 32 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 295 | blk.32.attn_v.weight | Block 32 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 296 | blk.32.ffn_down.weight | Block 32 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 297 | blk.32.ffn_gate.weight | Block 32 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 298 | blk.32.ffn_norm.weight | Block 32 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 299 | blk.32.ffn_up.weight | Block 32 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.32: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_33">Block 33 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 300 | blk.33.attn_k.weight | Block 33 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 301 | blk.33.attn_norm.weight | Block 33 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 302 | blk.33.attn_output.weight | Block 33 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 303 | blk.33.attn_q.weight | Block 33 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 304 | blk.33.attn_v.weight | Block 33 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 305 | blk.33.ffn_down.weight | Block 33 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 306 | blk.33.ffn_gate.weight | Block 33 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 307 | blk.33.ffn_norm.weight | Block 33 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 308 | blk.33.ffn_up.weight | Block 33 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.33: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_34">Block 34 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 309 | blk.34.attn_k.weight | Block 34 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 310 | blk.34.attn_norm.weight | Block 34 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 311 | blk.34.attn_output.weight | Block 34 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 312 | blk.34.attn_q.weight | Block 34 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 313 | blk.34.attn_v.weight | Block 34 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 314 | blk.34.ffn_down.weight | Block 34 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 315 | blk.34.ffn_gate.weight | Block 34 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 316 | blk.34.ffn_norm.weight | Block 34 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 317 | blk.34.ffn_up.weight | Block 34 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.34: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_35">Block 35 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 318 | blk.35.attn_k.weight | Block 35 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 319 | blk.35.attn_norm.weight | Block 35 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 320 | blk.35.attn_output.weight | Block 35 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 321 | blk.35.attn_q.weight | Block 35 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 322 | blk.35.attn_v.weight | Block 35 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 323 | blk.35.ffn_down.weight | Block 35 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 324 | blk.35.ffn_gate.weight | Block 35 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 325 | blk.35.ffn_norm.weight | Block 35 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 326 | blk.35.ffn_up.weight | Block 35 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.35: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_36">Block 36 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 327 | blk.36.attn_k.weight | Block 36 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 328 | blk.36.attn_norm.weight | Block 36 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 329 | blk.36.attn_output.weight | Block 36 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
|
|
| 330 | blk.36.attn_q.weight | Block 36 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
|
|
| 331 | blk.36.attn_v.weight | Block 36 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
|
|
| 332 | blk.36.ffn_down.weight | Block 36 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
|
|
| 333 | blk.36.ffn_gate.weight | Block 36 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
| 334 | blk.36.ffn_norm.weight | Block 36 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 335 | blk.36.ffn_up.weight | Block 36 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
|
|
|
|
- Total elements in blk.36: (~556M) 555755520
|
|
- Percentage of total elements: 2.47%
|
|
|
|
|
|
### <a name="blk_37">Block 37 Tensor Group : ~556M Elements</a>
|
|
|
|
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|
|
|-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----|
|
|
| 336 | blk.37.attn_k.weight | Block 37 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 337 | blk.37.attn_norm.weight | Block 37 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
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| 338 | blk.37.attn_output.weight | Block 37 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K |
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| 339 | blk.37.attn_q.weight | Block 37 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K |
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| 340 | blk.37.attn_v.weight | Block 37 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K |
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| 341 | blk.37.ffn_down.weight | Block 37 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K |
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| 342 | blk.37.ffn_gate.weight | Block 37 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
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| 343 | blk.37.ffn_norm.weight | Block 37 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
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| 344 | blk.37.ffn_up.weight | Block 37 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K |
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- Total elements in blk.37: (~556M) 555755520
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- Percentage of total elements: 2.47%
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