1155 lines
98 KiB
Markdown
1155 lines
98 KiB
Markdown
# Dolphin-Mistral-24B-Venice-Edition-pruned-Q3_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 | 12 |
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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-Q3\_K\_M.gguf - GGUF Internal File Dump](#Dolphin-Mistral-24B-Venice-Edition-pruned-q3_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 | 0x11300000 |
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| 1 | output_norm.weight | 0x11a84500 | 0x5000 |
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| 2 | token_embd.weight | 0x11a89500 | 0x11300000 |
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| 3 | blk.0.attn_k.weight | 0x22d89500 | 0x1a4000 |
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| 4 | blk.0.attn_norm.weight | 0x22f2d500 | 0x5000 |
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| 5 | blk.0.attn_output.weight | 0x22f32500 | 0xb40000 |
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| 6 | blk.0.attn_q.weight | 0x23a72500 | 0x690000 |
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| 7 | blk.0.attn_v.weight | 0x24102500 | 0x226000 |
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| 8 | blk.0.ffn_down.weight | 0x24328500 | 0x6e00000 |
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| 9 | blk.0.ffn_gate.weight | 0x2b128500 | 0x3480000 |
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| 10 | blk.0.ffn_norm.weight | 0x2e5a8500 | 0x5000 |
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| 11 | blk.0.ffn_up.weight | 0x2e5ad500 | 0x3480000 |
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| 12 | blk.1.attn_k.weight | 0x31a2d500 | 0x1a4000 |
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| 13 | blk.1.attn_norm.weight | 0x31bd1500 | 0x5000 |
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| 14 | blk.1.attn_output.weight | 0x31bd6500 | 0xb40000 |
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| 15 | blk.1.attn_q.weight | 0x32716500 | 0x690000 |
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| 16 | blk.1.attn_v.weight | 0x32da6500 | 0x226000 |
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| 17 | blk.1.ffn_down.weight | 0x32fcc500 | 0x6e00000 |
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| 18 | blk.1.ffn_gate.weight | 0x39dcc500 | 0x3480000 |
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| 19 | blk.1.ffn_norm.weight | 0x3d24c500 | 0x5000 |
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| 20 | blk.1.ffn_up.weight | 0x3d251500 | 0x3480000 |
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| 21 | blk.2.attn_k.weight | 0x406d1500 | 0x1a4000 |
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| 22 | blk.2.attn_norm.weight | 0x40875500 | 0x5000 |
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| 23 | blk.2.attn_output.weight | 0x4087a500 | 0xb40000 |
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| 24 | blk.2.attn_q.weight | 0x413ba500 | 0x690000 |
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| 25 | blk.2.attn_v.weight | 0x41a4a500 | 0x226000 |
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| 26 | blk.2.ffn_down.weight | 0x41c70500 | 0x5a00000 |
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| 27 | blk.2.ffn_gate.weight | 0x47670500 | 0x3480000 |
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| 28 | blk.2.ffn_norm.weight | 0x4aaf0500 | 0x5000 |
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| 29 | blk.2.ffn_up.weight | 0x4aaf5500 | 0x3480000 |
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| 30 | blk.3.attn_k.weight | 0x4df75500 | 0x1a4000 |
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| 31 | blk.3.attn_norm.weight | 0x4e119500 | 0x5000 |
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| 32 | blk.3.attn_output.weight | 0x4e11e500 | 0xb40000 |
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| 33 | blk.3.attn_q.weight | 0x4ec5e500 | 0x690000 |
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| 34 | blk.3.attn_v.weight | 0x4f2ee500 | 0x226000 |
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| 35 | blk.3.ffn_down.weight | 0x4f514500 | 0x5a00000 |
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| 36 | blk.3.ffn_gate.weight | 0x54f14500 | 0x3480000 |
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| 37 | blk.3.ffn_norm.weight | 0x58394500 | 0x5000 |
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| 38 | blk.3.ffn_up.weight | 0x58399500 | 0x3480000 |
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| 39 | blk.4.attn_k.weight | 0x5b819500 | 0x1a4000 |
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| 40 | blk.4.attn_norm.weight | 0x5b9bd500 | 0x5000 |
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| 41 | blk.4.attn_output.weight | 0x5b9c2500 | 0xb40000 |
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| 42 | blk.4.attn_q.weight | 0x5c502500 | 0x690000 |
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| 43 | blk.4.attn_v.weight | 0x5cb92500 | 0x226000 |
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| 44 | blk.4.ffn_down.weight | 0x5cdb8500 | 0x5a00000 |
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| 45 | blk.4.ffn_gate.weight | 0x627b8500 | 0x3480000 |
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| 46 | blk.4.ffn_norm.weight | 0x65c38500 | 0x5000 |
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| 47 | blk.4.ffn_up.weight | 0x65c3d500 | 0x3480000 |
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| 48 | blk.5.attn_k.weight | 0x690bd500 | 0x1a4000 |
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| 49 | blk.5.attn_norm.weight | 0x69261500 | 0x5000 |
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| 50 | blk.5.attn_output.weight | 0x69266500 | 0xb40000 |
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| 51 | blk.5.attn_q.weight | 0x69da6500 | 0x690000 |
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| 52 | blk.5.attn_v.weight | 0x6a436500 | 0x226000 |
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| 53 | blk.5.ffn_down.weight | 0x6a65c500 | 0x5a00000 |
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| 54 | blk.5.ffn_gate.weight | 0x7005c500 | 0x3480000 |
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| 55 | blk.5.ffn_norm.weight | 0x734dc500 | 0x5000 |
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| 56 | blk.5.ffn_up.weight | 0x734e1500 | 0x3480000 |
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| 57 | blk.6.attn_k.weight | 0x76961500 | 0x1a4000 |
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| 58 | blk.6.attn_norm.weight | 0x76b05500 | 0x5000 |
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| 59 | blk.6.attn_output.weight | 0x76b0a500 | 0xb40000 |
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| 60 | blk.6.attn_q.weight | 0x7764a500 | 0x690000 |
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| 61 | blk.6.attn_v.weight | 0x77cda500 | 0x226000 |
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| 62 | blk.6.ffn_down.weight | 0x77f00500 | 0x5a00000 |
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| 63 | blk.6.ffn_gate.weight | 0x7d900500 | 0x3480000 |
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| 64 | blk.6.ffn_norm.weight | 0x80d80500 | 0x5000 |
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| 65 | blk.6.ffn_up.weight | 0x80d85500 | 0x3480000 |
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| 66 | blk.7.attn_k.weight | 0x84205500 | 0x1a4000 |
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| 67 | blk.7.attn_norm.weight | 0x843a9500 | 0x5000 |
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| 68 | blk.7.attn_output.weight | 0x843ae500 | 0xb40000 |
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| 69 | blk.7.attn_q.weight | 0x84eee500 | 0x690000 |
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| 70 | blk.7.attn_v.weight | 0x8557e500 | 0x226000 |
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| 71 | blk.7.ffn_down.weight | 0x857a4500 | 0x5a00000 |
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| 72 | blk.7.ffn_gate.weight | 0x8b1a4500 | 0x3480000 |
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| 73 | blk.7.ffn_norm.weight | 0x8e624500 | 0x5000 |
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| 74 | blk.7.ffn_up.weight | 0x8e629500 | 0x3480000 |
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| 75 | blk.8.attn_k.weight | 0x91aa9500 | 0x1a4000 |
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| 76 | blk.8.attn_norm.weight | 0x91c4d500 | 0x5000 |
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| 77 | blk.8.attn_output.weight | 0x91c52500 | 0xb40000 |
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| 78 | blk.8.attn_q.weight | 0x92792500 | 0x690000 |
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| 79 | blk.8.attn_v.weight | 0x92e22500 | 0x226000 |
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| 80 | blk.8.ffn_down.weight | 0x93048500 | 0x5a00000 |
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| 81 | blk.8.ffn_gate.weight | 0x98a48500 | 0x3480000 |
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| 82 | blk.8.ffn_norm.weight | 0x9bec8500 | 0x5000 |
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| 83 | blk.8.ffn_up.weight | 0x9becd500 | 0x3480000 |
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| 84 | blk.9.attn_k.weight | 0x9f34d500 | 0x1a4000 |
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| 85 | blk.9.attn_norm.weight | 0x9f4f1500 | 0x5000 |
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| 86 | blk.9.attn_output.weight | 0x9f4f6500 | 0xb40000 |
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| 87 | blk.9.attn_q.weight | 0xa0036500 | 0x690000 |
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| 88 | blk.9.attn_v.weight | 0xa06c6500 | 0x226000 |
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| 89 | blk.9.ffn_down.weight | 0xa08ec500 | 0x5a00000 |
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| 90 | blk.9.ffn_gate.weight | 0xa62ec500 | 0x3480000 |
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| 91 | blk.9.ffn_norm.weight | 0xa976c500 | 0x5000 |
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| 92 | blk.9.ffn_up.weight | 0xa9771500 | 0x3480000 |
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| 93 | blk.10.attn_k.weight | 0xacbf1500 | 0x1a4000 |
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| 94 | blk.10.attn_norm.weight | 0xacd95500 | 0x5000 |
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| 95 | blk.10.attn_output.weight | 0xacd9a500 | 0xb40000 |
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| 96 | blk.10.attn_q.weight | 0xad8da500 | 0x690000 |
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| 97 | blk.10.attn_v.weight | 0xadf6a500 | 0x226000 |
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| 98 | blk.10.ffn_down.weight | 0xae190500 | 0x5a00000 |
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| 99 | blk.10.ffn_gate.weight | 0xb3b90500 | 0x3480000 |
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| 100 | blk.10.ffn_norm.weight | 0xb7010500 | 0x5000 |
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| 101 | blk.10.ffn_up.weight | 0xb7015500 | 0x3480000 |
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| 102 | blk.11.attn_k.weight | 0xba495500 | 0x1a4000 |
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| 103 | blk.11.attn_norm.weight | 0xba639500 | 0x5000 |
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| 104 | blk.11.attn_output.weight | 0xba63e500 | 0xb40000 |
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| 105 | blk.11.attn_q.weight | 0xbb17e500 | 0x690000 |
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| 106 | blk.11.attn_v.weight | 0xbb80e500 | 0x226000 |
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| 107 | blk.11.ffn_down.weight | 0xbba34500 | 0x5a00000 |
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| 108 | blk.11.ffn_gate.weight | 0xc1434500 | 0x3480000 |
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| 109 | blk.11.ffn_norm.weight | 0xc48b4500 | 0x5000 |
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| 110 | blk.11.ffn_up.weight | 0xc48b9500 | 0x3480000 |
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| 111 | blk.12.attn_k.weight | 0xc7d39500 | 0x1a4000 |
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| 112 | blk.12.attn_norm.weight | 0xc7edd500 | 0x5000 |
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| 113 | blk.12.attn_output.weight | 0xc7ee2500 | 0xb40000 |
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| 114 | blk.12.attn_q.weight | 0xc8a22500 | 0x690000 |
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| 115 | blk.12.attn_v.weight | 0xc90b2500 | 0x226000 |
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| 116 | blk.12.ffn_down.weight | 0xc92d8500 | 0x5a00000 |
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| 117 | blk.12.ffn_gate.weight | 0xcecd8500 | 0x3480000 |
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| 118 | blk.12.ffn_norm.weight | 0xd2158500 | 0x5000 |
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| 119 | blk.12.ffn_up.weight | 0xd215d500 | 0x3480000 |
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| 120 | blk.13.attn_k.weight | 0xd55dd500 | 0x1a4000 |
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| 121 | blk.13.attn_norm.weight | 0xd5781500 | 0x5000 |
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| 122 | blk.13.attn_output.weight | 0xd5786500 | 0xb40000 |
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| 123 | blk.13.attn_q.weight | 0xd62c6500 | 0x690000 |
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| 124 | blk.13.attn_v.weight | 0xd6956500 | 0x226000 |
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| 125 | blk.13.ffn_down.weight | 0xd6b7c500 | 0x5a00000 |
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| 126 | blk.13.ffn_gate.weight | 0xdc57c500 | 0x3480000 |
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| 127 | blk.13.ffn_norm.weight | 0xdf9fc500 | 0x5000 |
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| 128 | blk.13.ffn_up.weight | 0xdfa01500 | 0x3480000 |
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| 129 | blk.14.attn_k.weight | 0xe2e81500 | 0x1a4000 |
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| 130 | blk.14.attn_norm.weight | 0xe3025500 | 0x5000 |
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| 131 | blk.14.attn_output.weight | 0xe302a500 | 0xb40000 |
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| 132 | blk.14.attn_q.weight | 0xe3b6a500 | 0x690000 |
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| 133 | blk.14.attn_v.weight | 0xe41fa500 | 0x226000 |
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| 134 | blk.14.ffn_down.weight | 0xe4420500 | 0x5a00000 |
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| 135 | blk.14.ffn_gate.weight | 0xe9e20500 | 0x3480000 |
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| 136 | blk.14.ffn_norm.weight | 0xed2a0500 | 0x5000 |
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| 137 | blk.14.ffn_up.weight | 0xed2a5500 | 0x3480000 |
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| 138 | blk.15.attn_k.weight | 0xf0725500 | 0x1a4000 |
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| 139 | blk.15.attn_norm.weight | 0xf08c9500 | 0x5000 |
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| 140 | blk.15.attn_output.weight | 0xf08ce500 | 0xb40000 |
|
|
| 141 | blk.15.attn_q.weight | 0xf140e500 | 0x690000 |
|
|
| 142 | blk.15.attn_v.weight | 0xf1a9e500 | 0x226000 |
|
|
| 143 | blk.15.ffn_down.weight | 0xf1cc4500 | 0x5a00000 |
|
|
| 144 | blk.15.ffn_gate.weight | 0xf76c4500 | 0x3480000 |
|
|
| 145 | blk.15.ffn_norm.weight | 0xfab44500 | 0x5000 |
|
|
| 146 | blk.15.ffn_up.weight | 0xfab49500 | 0x3480000 |
|
|
| 147 | blk.16.attn_k.weight | 0xfdfc9500 | 0x1a4000 |
|
|
| 148 | blk.16.attn_norm.weight | 0xfe16d500 | 0x5000 |
|
|
| 149 | blk.16.attn_output.weight | 0xfe172500 | 0xb40000 |
|
|
| 150 | blk.16.attn_q.weight | 0xfecb2500 | 0x690000 |
|
|
| 151 | blk.16.attn_v.weight | 0xff342500 | 0x226000 |
|
|
| 152 | blk.16.ffn_down.weight | 0xff568500 | 0x5a00000 |
|
|
| 153 | blk.16.ffn_gate.weight | 0x104f68500 | 0x3480000 |
|
|
| 154 | blk.16.ffn_norm.weight | 0x1083e8500 | 0x5000 |
|
|
| 155 | blk.16.ffn_up.weight | 0x1083ed500 | 0x3480000 |
|
|
| 156 | blk.17.attn_k.weight | 0x10b86d500 | 0x226000 |
|
|
| 157 | blk.17.attn_norm.weight | 0x10ba93500 | 0x5000 |
|
|
| 158 | blk.17.attn_output.weight | 0x10ba98500 | 0xb40000 |
|
|
| 159 | blk.17.attn_q.weight | 0x10c5d8500 | 0x898000 |
|
|
| 160 | blk.17.attn_v.weight | 0x10ce70500 | 0x2d0000 |
|
|
| 161 | blk.17.ffn_down.weight | 0x10d140500 | 0x5a00000 |
|
|
| 162 | blk.17.ffn_gate.weight | 0x112b40500 | 0x3480000 |
|
|
| 163 | blk.17.ffn_norm.weight | 0x115fc0500 | 0x5000 |
|
|
| 164 | blk.17.ffn_up.weight | 0x115fc5500 | 0x3480000 |
|
|
| 165 | blk.18.attn_k.weight | 0x119445500 | 0x226000 |
|
|
| 166 | blk.18.attn_norm.weight | 0x11966b500 | 0x5000 |
|
|
| 167 | blk.18.attn_output.weight | 0x119670500 | 0xb40000 |
|
|
| 168 | blk.18.attn_q.weight | 0x11a1b0500 | 0x898000 |
|
|
| 169 | blk.18.attn_v.weight | 0x11aa48500 | 0x2d0000 |
|
|
| 170 | blk.18.ffn_down.weight | 0x11ad18500 | 0x5a00000 |
|
|
| 171 | blk.18.ffn_gate.weight | 0x120718500 | 0x3480000 |
|
|
| 172 | blk.18.ffn_norm.weight | 0x123b98500 | 0x5000 |
|
|
| 173 | blk.18.ffn_up.weight | 0x123b9d500 | 0x3480000 |
|
|
| 174 | blk.19.attn_k.weight | 0x12701d500 | 0x1a4000 |
|
|
| 175 | blk.19.attn_norm.weight | 0x1271c1500 | 0x5000 |
|
|
| 176 | blk.19.attn_output.weight | 0x1271c6500 | 0xb40000 |
|
|
| 177 | blk.19.attn_q.weight | 0x127d06500 | 0x690000 |
|
|
| 178 | blk.19.attn_v.weight | 0x128396500 | 0x226000 |
|
|
| 179 | blk.19.ffn_down.weight | 0x1285bc500 | 0x5a00000 |
|
|
| 180 | blk.19.ffn_gate.weight | 0x12dfbc500 | 0x3480000 |
|
|
| 181 | blk.19.ffn_norm.weight | 0x13143c500 | 0x5000 |
|
|
| 182 | blk.19.ffn_up.weight | 0x131441500 | 0x3480000 |
|
|
| 183 | blk.20.attn_k.weight | 0x1348c1500 | 0x226000 |
|
|
| 184 | blk.20.attn_norm.weight | 0x134ae7500 | 0x5000 |
|
|
| 185 | blk.20.attn_output.weight | 0x134aec500 | 0xb40000 |
|
|
| 186 | blk.20.attn_q.weight | 0x13562c500 | 0x898000 |
|
|
| 187 | blk.20.attn_v.weight | 0x135ec4500 | 0x2d0000 |
|
|
| 188 | blk.20.ffn_down.weight | 0x136194500 | 0x5a00000 |
|
|
| 189 | blk.20.ffn_gate.weight | 0x13bb94500 | 0x44c0000 |
|
|
| 190 | blk.20.ffn_norm.weight | 0x140054500 | 0x5000 |
|
|
| 191 | blk.20.ffn_up.weight | 0x140059500 | 0x44c0000 |
|
|
| 192 | blk.21.attn_k.weight | 0x144519500 | 0x1a4000 |
|
|
| 193 | blk.21.attn_norm.weight | 0x1446bd500 | 0x5000 |
|
|
| 194 | blk.21.attn_output.weight | 0x1446c2500 | 0xb40000 |
|
|
| 195 | blk.21.attn_q.weight | 0x145202500 | 0x690000 |
|
|
| 196 | blk.21.attn_v.weight | 0x145892500 | 0x226000 |
|
|
| 197 | blk.21.ffn_down.weight | 0x145ab8500 | 0x5a00000 |
|
|
| 198 | blk.21.ffn_gate.weight | 0x14b4b8500 | 0x44c0000 |
|
|
| 199 | blk.21.ffn_norm.weight | 0x14f978500 | 0x5000 |
|
|
| 200 | blk.21.ffn_up.weight | 0x14f97d500 | 0x44c0000 |
|
|
| 201 | blk.22.attn_k.weight | 0x153e3d500 | 0x226000 |
|
|
| 202 | blk.22.attn_norm.weight | 0x154063500 | 0x5000 |
|
|
| 203 | blk.22.attn_output.weight | 0x154068500 | 0xb40000 |
|
|
| 204 | blk.22.attn_q.weight | 0x154ba8500 | 0x898000 |
|
|
| 205 | blk.22.attn_v.weight | 0x155440500 | 0x2d0000 |
|
|
| 206 | blk.22.ffn_down.weight | 0x155710500 | 0x5a00000 |
|
|
| 207 | blk.22.ffn_gate.weight | 0x15b110500 | 0x44c0000 |
|
|
| 208 | blk.22.ffn_norm.weight | 0x15f5d0500 | 0x5000 |
|
|
| 209 | blk.22.ffn_up.weight | 0x15f5d5500 | 0x44c0000 |
|
|
| 210 | blk.23.attn_k.weight | 0x163a95500 | 0x226000 |
|
|
| 211 | blk.23.attn_norm.weight | 0x163cbb500 | 0x5000 |
|
|
| 212 | blk.23.attn_output.weight | 0x163cc0500 | 0xb40000 |
|
|
| 213 | blk.23.attn_q.weight | 0x164800500 | 0x898000 |
|
|
| 214 | blk.23.attn_v.weight | 0x165098500 | 0x2d0000 |
|
|
| 215 | blk.23.ffn_down.weight | 0x165368500 | 0x5a00000 |
|
|
| 216 | blk.23.ffn_gate.weight | 0x16ad68500 | 0x44c0000 |
|
|
| 217 | blk.23.ffn_norm.weight | 0x16f228500 | 0x5000 |
|
|
| 218 | blk.23.ffn_up.weight | 0x16f22d500 | 0x44c0000 |
|
|
| 219 | blk.24.attn_k.weight | 0x1736ed500 | 0x226000 |
|
|
| 220 | blk.24.attn_norm.weight | 0x173913500 | 0x5000 |
|
|
| 221 | blk.24.attn_output.weight | 0x173918500 | 0xb40000 |
|
|
| 222 | blk.24.attn_q.weight | 0x174458500 | 0x898000 |
|
|
| 223 | blk.24.attn_v.weight | 0x174cf0500 | 0x2d0000 |
|
|
| 224 | blk.24.ffn_down.weight | 0x174fc0500 | 0x5a00000 |
|
|
| 225 | blk.24.ffn_gate.weight | 0x17a9c0500 | 0x44c0000 |
|
|
| 226 | blk.24.ffn_norm.weight | 0x17ee80500 | 0x5000 |
|
|
| 227 | blk.24.ffn_up.weight | 0x17ee85500 | 0x44c0000 |
|
|
| 228 | blk.25.attn_k.weight | 0x183345500 | 0x226000 |
|
|
| 229 | blk.25.attn_norm.weight | 0x18356b500 | 0x5000 |
|
|
| 230 | blk.25.attn_output.weight | 0x183570500 | 0xb40000 |
|
|
| 231 | blk.25.attn_q.weight | 0x1840b0500 | 0x898000 |
|
|
| 232 | blk.25.attn_v.weight | 0x184948500 | 0x2d0000 |
|
|
| 233 | blk.25.ffn_down.weight | 0x184c18500 | 0x5a00000 |
|
|
| 234 | blk.25.ffn_gate.weight | 0x18a618500 | 0x44c0000 |
|
|
| 235 | blk.25.ffn_norm.weight | 0x18ead8500 | 0x5000 |
|
|
| 236 | blk.25.ffn_up.weight | 0x18eadd500 | 0x44c0000 |
|
|
| 237 | blk.26.attn_k.weight | 0x192f9d500 | 0x226000 |
|
|
| 238 | blk.26.attn_norm.weight | 0x1931c3500 | 0x5000 |
|
|
| 239 | blk.26.attn_output.weight | 0x1931c8500 | 0xb40000 |
|
|
| 240 | blk.26.attn_q.weight | 0x193d08500 | 0x898000 |
|
|
| 241 | blk.26.attn_v.weight | 0x1945a0500 | 0x2d0000 |
|
|
| 242 | blk.26.ffn_down.weight | 0x194870500 | 0x5a00000 |
|
|
| 243 | blk.26.ffn_gate.weight | 0x19a270500 | 0x44c0000 |
|
|
| 244 | blk.26.ffn_norm.weight | 0x19e730500 | 0x5000 |
|
|
| 245 | blk.26.ffn_up.weight | 0x19e735500 | 0x44c0000 |
|
|
| 246 | blk.27.attn_k.weight | 0x1a2bf5500 | 0x1a4000 |
|
|
| 247 | blk.27.attn_norm.weight | 0x1a2d99500 | 0x5000 |
|
|
| 248 | blk.27.attn_output.weight | 0x1a2d9e500 | 0xb40000 |
|
|
| 249 | blk.27.attn_q.weight | 0x1a38de500 | 0x690000 |
|
|
| 250 | blk.27.attn_v.weight | 0x1a3f6e500 | 0x226000 |
|
|
| 251 | blk.27.ffn_down.weight | 0x1a4194500 | 0x5a00000 |
|
|
| 252 | blk.27.ffn_gate.weight | 0x1a9b94500 | 0x44c0000 |
|
|
| 253 | blk.27.ffn_norm.weight | 0x1ae054500 | 0x5000 |
|
|
| 254 | blk.27.ffn_up.weight | 0x1ae059500 | 0x44c0000 |
|
|
| 255 | blk.28.attn_k.weight | 0x1b2519500 | 0x226000 |
|
|
| 256 | blk.28.attn_norm.weight | 0x1b273f500 | 0x5000 |
|
|
| 257 | blk.28.attn_output.weight | 0x1b2744500 | 0xb40000 |
|
|
| 258 | blk.28.attn_q.weight | 0x1b3284500 | 0x898000 |
|
|
| 259 | blk.28.attn_v.weight | 0x1b3b1c500 | 0x2d0000 |
|
|
| 260 | blk.28.ffn_down.weight | 0x1b3dec500 | 0x5a00000 |
|
|
| 261 | blk.28.ffn_gate.weight | 0x1b97ec500 | 0x44c0000 |
|
|
| 262 | blk.28.ffn_norm.weight | 0x1bdcac500 | 0x5000 |
|
|
| 263 | blk.28.ffn_up.weight | 0x1bdcb1500 | 0x44c0000 |
|
|
| 264 | blk.29.attn_k.weight | 0x1c2171500 | 0x226000 |
|
|
| 265 | blk.29.attn_norm.weight | 0x1c2397500 | 0x5000 |
|
|
| 266 | blk.29.attn_output.weight | 0x1c239c500 | 0xb40000 |
|
|
| 267 | blk.29.attn_q.weight | 0x1c2edc500 | 0x898000 |
|
|
| 268 | blk.29.attn_v.weight | 0x1c3774500 | 0x2d0000 |
|
|
| 269 | blk.29.ffn_down.weight | 0x1c3a44500 | 0x5a00000 |
|
|
| 270 | blk.29.ffn_gate.weight | 0x1c9444500 | 0x44c0000 |
|
|
| 271 | blk.29.ffn_norm.weight | 0x1cd904500 | 0x5000 |
|
|
| 272 | blk.29.ffn_up.weight | 0x1cd909500 | 0x44c0000 |
|
|
| 273 | blk.30.attn_k.weight | 0x1d1dc9500 | 0x226000 |
|
|
| 274 | blk.30.attn_norm.weight | 0x1d1fef500 | 0x5000 |
|
|
| 275 | blk.30.attn_output.weight | 0x1d1ff4500 | 0xb40000 |
|
|
| 276 | blk.30.attn_q.weight | 0x1d2b34500 | 0x898000 |
|
|
| 277 | blk.30.attn_v.weight | 0x1d33cc500 | 0x2d0000 |
|
|
| 278 | blk.30.ffn_down.weight | 0x1d369c500 | 0x5a00000 |
|
|
| 279 | blk.30.ffn_gate.weight | 0x1d909c500 | 0x44c0000 |
|
|
| 280 | blk.30.ffn_norm.weight | 0x1dd55c500 | 0x5000 |
|
|
| 281 | blk.30.ffn_up.weight | 0x1dd561500 | 0x44c0000 |
|
|
| 282 | blk.31.attn_k.weight | 0x1e1a21500 | 0x226000 |
|
|
| 283 | blk.31.attn_norm.weight | 0x1e1c47500 | 0x5000 |
|
|
| 284 | blk.31.attn_output.weight | 0x1e1c4c500 | 0xb40000 |
|
|
| 285 | blk.31.attn_q.weight | 0x1e278c500 | 0x898000 |
|
|
| 286 | blk.31.attn_v.weight | 0x1e3024500 | 0x2d0000 |
|
|
| 287 | blk.31.ffn_down.weight | 0x1e32f4500 | 0x5a00000 |
|
|
| 288 | blk.31.ffn_gate.weight | 0x1e8cf4500 | 0x44c0000 |
|
|
| 289 | blk.31.ffn_norm.weight | 0x1ed1b4500 | 0x5000 |
|
|
| 290 | blk.31.ffn_up.weight | 0x1ed1b9500 | 0x44c0000 |
|
|
| 291 | blk.32.attn_k.weight | 0x1f1679500 | 0x226000 |
|
|
| 292 | blk.32.attn_norm.weight | 0x1f189f500 | 0x5000 |
|
|
| 293 | blk.32.attn_output.weight | 0x1f18a4500 | 0xb40000 |
|
|
| 294 | blk.32.attn_q.weight | 0x1f23e4500 | 0x898000 |
|
|
| 295 | blk.32.attn_v.weight | 0x1f2c7c500 | 0x2d0000 |
|
|
| 296 | blk.32.ffn_down.weight | 0x1f2f4c500 | 0x5a00000 |
|
|
| 297 | blk.32.ffn_gate.weight | 0x1f894c500 | 0x44c0000 |
|
|
| 298 | blk.32.ffn_norm.weight | 0x1fce0c500 | 0x5000 |
|
|
| 299 | blk.32.ffn_up.weight | 0x1fce11500 | 0x44c0000 |
|
|
| 300 | blk.33.attn_k.weight | 0x2012d1500 | 0x226000 |
|
|
| 301 | blk.33.attn_norm.weight | 0x2014f7500 | 0x5000 |
|
|
| 302 | blk.33.attn_output.weight | 0x2014fc500 | 0xb40000 |
|
|
| 303 | blk.33.attn_q.weight | 0x20203c500 | 0x898000 |
|
|
| 304 | blk.33.attn_v.weight | 0x2028d4500 | 0x2d0000 |
|
|
| 305 | blk.33.ffn_down.weight | 0x202ba4500 | 0x5a00000 |
|
|
| 306 | blk.33.ffn_gate.weight | 0x2085a4500 | 0x44c0000 |
|
|
| 307 | blk.33.ffn_norm.weight | 0x20ca64500 | 0x5000 |
|
|
| 308 | blk.33.ffn_up.weight | 0x20ca69500 | 0x44c0000 |
|
|
| 309 | blk.34.attn_k.weight | 0x210f29500 | 0x226000 |
|
|
| 310 | blk.34.attn_norm.weight | 0x21114f500 | 0x5000 |
|
|
| 311 | blk.34.attn_output.weight | 0x211154500 | 0xb40000 |
|
|
| 312 | blk.34.attn_q.weight | 0x211c94500 | 0x898000 |
|
|
| 313 | blk.34.attn_v.weight | 0x21252c500 | 0x2d0000 |
|
|
| 314 | blk.34.ffn_down.weight | 0x2127fc500 | 0x5a00000 |
|
|
| 315 | blk.34.ffn_gate.weight | 0x2181fc500 | 0x44c0000 |
|
|
| 316 | blk.34.ffn_norm.weight | 0x21c6bc500 | 0x5000 |
|
|
| 317 | blk.34.ffn_up.weight | 0x21c6c1500 | 0x44c0000 |
|
|
| 318 | blk.35.attn_k.weight | 0x220b81500 | 0x226000 |
|
|
| 319 | blk.35.attn_norm.weight | 0x220da7500 | 0x5000 |
|
|
| 320 | blk.35.attn_output.weight | 0x220dac500 | 0xb40000 |
|
|
| 321 | blk.35.attn_q.weight | 0x2218ec500 | 0x898000 |
|
|
| 322 | blk.35.attn_v.weight | 0x222184500 | 0x2d0000 |
|
|
| 323 | blk.35.ffn_down.weight | 0x222454500 | 0x5a00000 |
|
|
| 324 | blk.35.ffn_gate.weight | 0x227e54500 | 0x44c0000 |
|
|
| 325 | blk.35.ffn_norm.weight | 0x22c314500 | 0x5000 |
|
|
| 326 | blk.35.ffn_up.weight | 0x22c319500 | 0x44c0000 |
|
|
| 327 | blk.36.attn_k.weight | 0x2307d9500 | 0x226000 |
|
|
| 328 | blk.36.attn_norm.weight | 0x2309ff500 | 0x5000 |
|
|
| 329 | blk.36.attn_output.weight | 0x230a04500 | 0xb40000 |
|
|
| 330 | blk.36.attn_q.weight | 0x231544500 | 0x898000 |
|
|
| 331 | blk.36.attn_v.weight | 0x231ddc500 | 0x2d0000 |
|
|
| 332 | blk.36.ffn_down.weight | 0x2320ac500 | 0x5a00000 |
|
|
| 333 | blk.36.ffn_gate.weight | 0x237aac500 | 0x44c0000 |
|
|
| 334 | blk.36.ffn_norm.weight | 0x23bf6c500 | 0x5000 |
|
|
| 335 | blk.36.ffn_up.weight | 0x23bf71500 | 0x44c0000 |
|
|
| 336 | blk.37.attn_k.weight | 0x240431500 | 0x226000 |
|
|
| 337 | blk.37.attn_norm.weight | 0x240657500 | 0x5000 |
|
|
| 338 | blk.37.attn_output.weight | 0x24065c500 | 0xb40000 |
|
|
| 339 | blk.37.attn_q.weight | 0x24119c500 | 0x898000 |
|
|
| 340 | blk.37.attn_v.weight | 0x241a34500 | 0x2d0000 |
|
|
| 341 | blk.37.ffn_down.weight | 0x241d04500 | 0x5a00000 |
|
|
| 342 | blk.37.ffn_gate.weight | 0x247704500 | 0x44c0000 |
|
|
| 343 | blk.37.ffn_norm.weight | 0x24bbc4500 | 0x5000 |
|
|
| 344 | blk.37.ffn_up.weight | 0x24bbc9500 | 0x44c0000 |
|
|
|
|
### <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 | Q3_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 | Q2_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 | Q2_K |
|
|
| 7 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 8 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K |
|
|
| 9 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 16 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 17 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K |
|
|
| 18 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 25 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 26 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 27 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 34 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 35 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 36 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 43 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 44 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 45 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 52 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_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 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 61 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_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 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 70 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 71 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 72 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 79 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_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 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 88 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_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 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 97 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 98 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 99 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 106 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_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 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 115 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_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 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 124 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 125 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 126 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 133 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_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 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 142 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_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 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 151 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 152 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 153 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q2_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 | Q2_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 | Q3_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 | Q3_K |
|
|
| 160 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_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 | Q2_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 | Q2_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 | Q3_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 | Q3_K |
|
|
| 169 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_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 | Q2_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 | Q2_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 | Q2_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 | Q2_K |
|
|
| 178 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K |
|
|
| 179 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 180 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q2_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 | Q2_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 | Q3_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 | Q3_K |
|
|
| 187 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_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 | Q3_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 | Q3_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 | Q2_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 | Q2_K |
|
|
| 196 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_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 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 205 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 206 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 207 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 214 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_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 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 223 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_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 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 232 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 233 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 234 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 241 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_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 | Q3_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 | Q3_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 | Q2_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 | Q2_K |
|
|
| 250 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_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 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 259 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 260 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 261 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 268 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_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 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 277 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_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 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 286 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 287 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 288 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 295 | blk.32.attn_v.weight | Block 32 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_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 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 304 | blk.33.attn_v.weight | Block 33 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_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 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 313 | blk.34.attn_v.weight | Block 34 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 314 | blk.34.ffn_down.weight | Block 34 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 315 | blk.34.ffn_gate.weight | Block 34 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 322 | blk.35.attn_v.weight | Block 35 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 323 | blk.35.ffn_down.weight | Block 35 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 324 | blk.35.ffn_gate.weight | Block 35 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_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 | Q3_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 | Q3_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 | Q3_K |
|
|
| 331 | blk.36.attn_v.weight | Block 36 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K |
|
|
| 332 | blk.36.ffn_down.weight | Block 36 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q4_K |
|
|
| 333 | blk.36.ffn_gate.weight | Block 36 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_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 | Q3_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 | Q3_K |
|
|
| 337 | blk.37.attn_norm.weight | Block 37 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 |
|
|
| 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 | Q3_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 | Q4_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 | Q4_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 | Q3_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 | Q3_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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