eaddario/Watt-Tool-8B-GGUF
1
0
Fork 0
Code Issues Pull Requests Actions Projects Releases Wiki Activity
Files
main
Watt-Tool-8B-GGUF/scores/Watt-Tool-8B-IQ3_M.md
ModelHub XC f9723b838e 初始化项目，由ModelHub XC社区提供模型 
Model: eaddario/Watt-Tool-8B-GGUF
Source: Original Platform
2026-07-21 16:00:13 +08:00

983 lines
84 KiB
Markdown
Raw Permalink Blame History

# Watt-Tool-8B-IQ3_M.gguf - GGUF Internal File Dump
- Endian: LITTLE endian
## Key Value Metadata Store
There are 43 key-value pairs in this file
| POS | TYPE | Count | Key | Value |
|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
| 1 | UINT32 | 1 | GGUF.version | 3 |
| 2 | UINT64 | 1 | GGUF.tensor_count | 292 |
| 3 | UINT64 | 1 | GGUF.kv_count | 40 |
| 4 | STRING | 1 | general.architecture | `llama` |
| 5 | STRING | 1 | general.type | `model` |
| 6 | STRING | 1 | general.name | `Watt Tool 8B GGUF` |
| 7 | STRING | 1 | general.finetune | `GGUF` |
| 8 | STRING | 1 | general.basename | `Watt-Tool` |
| 9 | STRING | 1 | general.size_label | `8B` |
| 10 | STRING | 1 | general.license | `apache-2.0` |
| 11 | UINT32 | 1 | general.base_model.count | 1 |
| 12 | STRING | 1 | general.base_model.0.name | `Llama 3.1 8B Instruct` |
| 13 | STRING | 1 | general.base_model.0.organization | `Meta Llama` |
| 14 | STRING | 1 | general.base_model.0.repo_url | `https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct` |
| 15 | [STRING] | 4 | general.tags | [ `function-calling`, `tool-use`, `llama`, `bfcl` ] |
| 16 | [STRING] | 1 | general.languages | [ `en` ] |
| 17 | UINT32 | 1 | llama.block_count | 32 |
| 18 | UINT32 | 1 | llama.context_length | 131072 |
| 19 | UINT32 | 1 | llama.embedding_length | 4096 |
| 20 | UINT32 | 1 | llama.feed_forward_length | 14336 |
| 21 | UINT32 | 1 | llama.attention.head_count | 32 |
| 22 | UINT32 | 1 | llama.attention.head_count_kv | 8 |
| 23 | FLOAT32 | 1 | llama.rope.freq_base | 500000.0 |
| 24 | FLOAT32 | 1 | llama.attention.layer_norm_rms_epsilon | 1e-05 |
| 25 | UINT32 | 1 | llama.attention.key_length | 128 |
| 26 | UINT32 | 1 | llama.attention.value_length | 128 |
| 27 | UINT32 | 1 | llama.vocab_size | 128256 |
| 28 | UINT32 | 1 | llama.rope.dimension_count | 128 |
| 29 | STRING | 1 | tokenizer.ggml.model | `gpt2` |
| 30 | STRING | 1 | tokenizer.ggml.pre | `llama-bpe` |
| 31 | [STRING] | 128256 | tokenizer.ggml.tokens | [ `!`, `"`, `#`, `$`, `%`, ... ] |
| 32 | [INT32] | 128256 | tokenizer.ggml.token_type | [ 1, 1, 1, 1, 1, 1, 1, ... ] |
| 33 | [STRING] | 280147 | tokenizer.ggml.merges | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ] |
| 34 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 128000 |
| 35 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 128009 |
| 36 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 128009 |
| 37 | STRING | 1 | tokenizer.chat_template | `{{ '<|begin_of_text|>' }}{% if`...`d|>' }}{% endif %}{% endfor %}` |
| 38 | UINT32 | 1 | general.quantization_version | 2 |
| 39 | UINT32 | 1 | general.file_type | 27 |
| 40 | STRING | 1 | quantize.imatrix.file | `./imatrix/imatrix-Watt-Tool-8B-small.dat` |
| 41 | STRING | 1 | quantize.imatrix.dataset | `../../datasets/imatrix/calibration_eur_small.txt` |
| 42 | INT32 | 1 | quantize.imatrix.entries_count | 225 |
| 43 | INT32 | 1 | quantize.imatrix.chunks_count | 962 |
## Tensors Overview ~8B Elements
Total number of elements in all tensors: 8030261312 Elements
- [Watt-Tool-8B-IQ3\_M.gguf - GGUF Internal File Dump](#watt-tool-8b-iq3_mgguf---gguf-internal-file-dump)
- [Key Value Metadata Store](#key-value-metadata-store)
- [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
- [Tensor Data Offset](#tensor-data-offset)
- [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
- [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
- [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
- [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
- [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
- [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
- [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
- [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
- [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
- [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
- [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
- [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
- [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
- [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
- [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
- [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
- [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
- [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
- [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
- [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
- [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
- [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
- [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
- [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
- [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
- [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
- [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
- [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
- [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
- [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
- [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
- [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
- [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
### Tensor Data Offset
This table contains the offset and data segment relative to start of file
| T_ID | Tensor Layer Name | Data Offset (B) | Data Size (B) |
|-----:|:--------------------------|-----------------:|-----------------:|
| 0 | output.weight | 0x779620 | 0xd746000 |
| 1 | output_norm.weight | 0xdebf620 | 0x4000 |
| 2 | rope_freqs.weight | 0xdec3620 | 0x100 |
| 3 | token_embd.weight | 0xdec3720 | 0xd746000 |
| 4 | blk.0.attn_k.weight | 0x1b609720 | 0x188000 |
| 5 | blk.0.attn_norm.weight | 0x1b791720 | 0x4000 |
| 6 | blk.0.attn_output.weight | 0x1b795720 | 0x900000 |
| 7 | blk.0.attn_q.weight | 0x1c095720 | 0x620000 |
| 8 | blk.0.attn_v.weight | 0x1c6b5720 | 0x1b8000 |
| 9 | blk.0.ffn_down.weight | 0x1c86d720 | 0x1f80000 |
| 10 | blk.0.ffn_gate.weight | 0x1e7ed720 | 0x1570000 |
| 11 | blk.0.ffn_norm.weight | 0x1fd5d720 | 0x4000 |
| 12 | blk.0.ffn_up.weight | 0x1fd61720 | 0x1570000 |
| 13 | blk.1.attn_k.weight | 0x212d1720 | 0x188000 |
| 14 | blk.1.attn_norm.weight | 0x21459720 | 0x4000 |
| 15 | blk.1.attn_output.weight | 0x2145d720 | 0x900000 |
| 16 | blk.1.attn_q.weight | 0x21d5d720 | 0x620000 |
| 17 | blk.1.attn_v.weight | 0x2237d720 | 0x1b8000 |
| 18 | blk.1.ffn_down.weight | 0x22535720 | 0x1f80000 |
| 19 | blk.1.ffn_gate.weight | 0x244b5720 | 0x1570000 |
| 20 | blk.1.ffn_norm.weight | 0x25a25720 | 0x4000 |
| 21 | blk.1.ffn_up.weight | 0x25a29720 | 0x1570000 |
| 22 | blk.2.attn_k.weight | 0x26f99720 | 0x188000 |
| 23 | blk.2.attn_norm.weight | 0x27121720 | 0x4000 |
| 24 | blk.2.attn_output.weight | 0x27125720 | 0x900000 |
| 25 | blk.2.attn_q.weight | 0x27a25720 | 0x620000 |
| 26 | blk.2.attn_v.weight | 0x28045720 | 0x1b8000 |
| 27 | blk.2.ffn_down.weight | 0x281fd720 | 0x1f80000 |
| 28 | blk.2.ffn_gate.weight | 0x2a17d720 | 0x1570000 |
| 29 | blk.2.ffn_norm.weight | 0x2b6ed720 | 0x4000 |
| 30 | blk.2.ffn_up.weight | 0x2b6f1720 | 0x1570000 |
| 31 | blk.3.attn_k.weight | 0x2cc61720 | 0x188000 |
| 32 | blk.3.attn_norm.weight | 0x2cde9720 | 0x4000 |
| 33 | blk.3.attn_output.weight | 0x2cded720 | 0x900000 |
| 34 | blk.3.attn_q.weight | 0x2d6ed720 | 0x620000 |
| 35 | blk.3.attn_v.weight | 0x2dd0d720 | 0x1b8000 |
| 36 | blk.3.ffn_down.weight | 0x2dec5720 | 0x1f80000 |
| 37 | blk.3.ffn_gate.weight | 0x2fe45720 | 0x1570000 |
| 38 | blk.3.ffn_norm.weight | 0x313b5720 | 0x4000 |
| 39 | blk.3.ffn_up.weight | 0x313b9720 | 0x1570000 |
| 40 | blk.4.attn_k.weight | 0x32929720 | 0x188000 |
| 41 | blk.4.attn_norm.weight | 0x32ab1720 | 0x4000 |
| 42 | blk.4.attn_output.weight | 0x32ab5720 | 0x900000 |
| 43 | blk.4.attn_q.weight | 0x333b5720 | 0x620000 |
| 44 | blk.4.attn_v.weight | 0x339d5720 | 0x1b8000 |
| 45 | blk.4.ffn_down.weight | 0x33b8d720 | 0x1f80000 |
| 46 | blk.4.ffn_gate.weight | 0x35b0d720 | 0x1570000 |
| 47 | blk.4.ffn_norm.weight | 0x3707d720 | 0x4000 |
| 48 | blk.4.ffn_up.weight | 0x37081720 | 0x1570000 |
| 49 | blk.5.attn_k.weight | 0x385f1720 | 0x188000 |
| 50 | blk.5.attn_norm.weight | 0x38779720 | 0x4000 |
| 51 | blk.5.attn_output.weight | 0x3877d720 | 0x900000 |
| 52 | blk.5.attn_q.weight | 0x3907d720 | 0x620000 |
| 53 | blk.5.attn_v.weight | 0x3969d720 | 0x1b8000 |
| 54 | blk.5.ffn_down.weight | 0x39855720 | 0x1f80000 |
| 55 | blk.5.ffn_gate.weight | 0x3b7d5720 | 0x1570000 |
| 56 | blk.5.ffn_norm.weight | 0x3cd45720 | 0x4000 |
| 57 | blk.5.ffn_up.weight | 0x3cd49720 | 0x1570000 |
| 58 | blk.6.attn_k.weight | 0x3e2b9720 | 0x188000 |
| 59 | blk.6.attn_norm.weight | 0x3e441720 | 0x4000 |
| 60 | blk.6.attn_output.weight | 0x3e445720 | 0x900000 |
| 61 | blk.6.attn_q.weight | 0x3ed45720 | 0x620000 |
| 62 | blk.6.attn_v.weight | 0x3f365720 | 0x1b8000 |
| 63 | blk.6.ffn_down.weight | 0x3f51d720 | 0x1f80000 |
| 64 | blk.6.ffn_gate.weight | 0x4149d720 | 0x1570000 |
| 65 | blk.6.ffn_norm.weight | 0x42a0d720 | 0x4000 |
| 66 | blk.6.ffn_up.weight | 0x42a11720 | 0x1570000 |
| 67 | blk.7.attn_k.weight | 0x43f81720 | 0x188000 |
| 68 | blk.7.attn_norm.weight | 0x44109720 | 0x4000 |
| 69 | blk.7.attn_output.weight | 0x4410d720 | 0x900000 |
| 70 | blk.7.attn_q.weight | 0x44a0d720 | 0x620000 |
| 71 | blk.7.attn_v.weight | 0x4502d720 | 0x1b8000 |
| 72 | blk.7.ffn_down.weight | 0x451e5720 | 0x1f80000 |
| 73 | blk.7.ffn_gate.weight | 0x47165720 | 0x1570000 |
| 74 | blk.7.ffn_norm.weight | 0x486d5720 | 0x4000 |
| 75 | blk.7.ffn_up.weight | 0x486d9720 | 0x1570000 |
| 76 | blk.8.attn_k.weight | 0x49c49720 | 0x188000 |
| 77 | blk.8.attn_norm.weight | 0x49dd1720 | 0x4000 |
| 78 | blk.8.attn_output.weight | 0x49dd5720 | 0x900000 |
| 79 | blk.8.attn_q.weight | 0x4a6d5720 | 0x620000 |
| 80 | blk.8.attn_v.weight | 0x4acf5720 | 0x1b8000 |
| 81 | blk.8.ffn_down.weight | 0x4aead720 | 0x1f80000 |
| 82 | blk.8.ffn_gate.weight | 0x4ce2d720 | 0x1570000 |
| 83 | blk.8.ffn_norm.weight | 0x4e39d720 | 0x4000 |
| 84 | blk.8.ffn_up.weight | 0x4e3a1720 | 0x1570000 |
| 85 | blk.9.attn_k.weight | 0x4f911720 | 0x188000 |
| 86 | blk.9.attn_norm.weight | 0x4fa99720 | 0x4000 |
| 87 | blk.9.attn_output.weight | 0x4fa9d720 | 0x900000 |
| 88 | blk.9.attn_q.weight | 0x5039d720 | 0x620000 |
| 89 | blk.9.attn_v.weight | 0x509bd720 | 0x1b8000 |
| 90 | blk.9.ffn_down.weight | 0x50b75720 | 0x1f80000 |
| 91 | blk.9.ffn_gate.weight | 0x52af5720 | 0x1570000 |
| 92 | blk.9.ffn_norm.weight | 0x54065720 | 0x4000 |
| 93 | blk.9.ffn_up.weight | 0x54069720 | 0x1570000 |
| 94 | blk.10.attn_k.weight | 0x555d9720 | 0x188000 |
| 95 | blk.10.attn_norm.weight | 0x55761720 | 0x4000 |
| 96 | blk.10.attn_output.weight | 0x55765720 | 0x900000 |
| 97 | blk.10.attn_q.weight | 0x56065720 | 0x620000 |
| 98 | blk.10.attn_v.weight | 0x56685720 | 0x1b8000 |
| 99 | blk.10.ffn_down.weight | 0x5683d720 | 0x1f80000 |
| 100 | blk.10.ffn_gate.weight | 0x587bd720 | 0x1570000 |
| 101 | blk.10.ffn_norm.weight | 0x59d2d720 | 0x4000 |
| 102 | blk.10.ffn_up.weight | 0x59d31720 | 0x1570000 |
| 103 | blk.11.attn_k.weight | 0x5b2a1720 | 0x188000 |
| 104 | blk.11.attn_norm.weight | 0x5b429720 | 0x4000 |
| 105 | blk.11.attn_output.weight | 0x5b42d720 | 0x900000 |
| 106 | blk.11.attn_q.weight | 0x5bd2d720 | 0x620000 |
| 107 | blk.11.attn_v.weight | 0x5c34d720 | 0x1b8000 |
| 108 | blk.11.ffn_down.weight | 0x5c505720 | 0x1f80000 |
| 109 | blk.11.ffn_gate.weight | 0x5e485720 | 0x1570000 |
| 110 | blk.11.ffn_norm.weight | 0x5f9f5720 | 0x4000 |
| 111 | blk.11.ffn_up.weight | 0x5f9f9720 | 0x1570000 |
| 112 | blk.12.attn_k.weight | 0x60f69720 | 0x188000 |
| 113 | blk.12.attn_norm.weight | 0x610f1720 | 0x4000 |
| 114 | blk.12.attn_output.weight | 0x610f5720 | 0x900000 |
| 115 | blk.12.attn_q.weight | 0x619f5720 | 0x620000 |
| 116 | blk.12.attn_v.weight | 0x62015720 | 0x1b8000 |
| 117 | blk.12.ffn_down.weight | 0x621cd720 | 0x1f80000 |
| 118 | blk.12.ffn_gate.weight | 0x6414d720 | 0x1570000 |
| 119 | blk.12.ffn_norm.weight | 0x656bd720 | 0x4000 |
| 120 | blk.12.ffn_up.weight | 0x656c1720 | 0x1570000 |
| 121 | blk.13.attn_k.weight | 0x66c31720 | 0x1b8000 |
| 122 | blk.13.attn_norm.weight | 0x66de9720 | 0x4000 |
| 123 | blk.13.attn_output.weight | 0x66ded720 | 0x900000 |
| 124 | blk.13.attn_q.weight | 0x676ed720 | 0x6e0000 |
| 125 | blk.13.attn_v.weight | 0x67dcd720 | 0x240000 |
| 126 | blk.13.ffn_down.weight | 0x6800d720 | 0x1f80000 |
| 127 | blk.13.ffn_gate.weight | 0x69f8d720 | 0x1570000 |
| 128 | blk.13.ffn_norm.weight | 0x6b4fd720 | 0x4000 |
| 129 | blk.13.ffn_up.weight | 0x6b501720 | 0x1570000 |
| 130 | blk.14.attn_k.weight | 0x6ca71720 | 0x1b8000 |
| 131 | blk.14.attn_norm.weight | 0x6cc29720 | 0x4000 |
| 132 | blk.14.attn_output.weight | 0x6cc2d720 | 0x900000 |
| 133 | blk.14.attn_q.weight | 0x6d52d720 | 0x6e0000 |
| 134 | blk.14.attn_v.weight | 0x6dc0d720 | 0x240000 |
| 135 | blk.14.ffn_down.weight | 0x6de4d720 | 0x1f80000 |
| 136 | blk.14.ffn_gate.weight | 0x6fdcd720 | 0x1570000 |
| 137 | blk.14.ffn_norm.weight | 0x7133d720 | 0x4000 |
| 138 | blk.14.ffn_up.weight | 0x71341720 | 0x1570000 |
| 139 | blk.15.attn_k.weight | 0x728b1720 | 0x188000 |
| 140 | blk.15.attn_norm.weight | 0x72a39720 | 0x4000 |
| 141 | blk.15.attn_output.weight | 0x72a3d720 | 0x900000 |
| 142 | blk.15.attn_q.weight | 0x7333d720 | 0x620000 |
| 143 | blk.15.attn_v.weight | 0x7395d720 | 0x1b8000 |
| 144 | blk.15.ffn_down.weight | 0x73b15720 | 0x1f80000 |
| 145 | blk.15.ffn_gate.weight | 0x75a95720 | 0x1570000 |
| 146 | blk.15.ffn_norm.weight | 0x77005720 | 0x4000 |
| 147 | blk.15.ffn_up.weight | 0x77009720 | 0x1570000 |
| 148 | blk.16.attn_k.weight | 0x78579720 | 0x1b8000 |
| 149 | blk.16.attn_norm.weight | 0x78731720 | 0x4000 |
| 150 | blk.16.attn_output.weight | 0x78735720 | 0x900000 |
| 151 | blk.16.attn_q.weight | 0x79035720 | 0x6e0000 |
| 152 | blk.16.attn_v.weight | 0x79715720 | 0x240000 |
| 153 | blk.16.ffn_down.weight | 0x79955720 | 0x1f80000 |
| 154 | blk.16.ffn_gate.weight | 0x7b8d5720 | 0x1810000 |
| 155 | blk.16.ffn_norm.weight | 0x7d0e5720 | 0x4000 |
| 156 | blk.16.ffn_up.weight | 0x7d0e9720 | 0x1810000 |
| 157 | blk.17.attn_k.weight | 0x7e8f9720 | 0x188000 |
| 158 | blk.17.attn_norm.weight | 0x7ea81720 | 0x4000 |
| 159 | blk.17.attn_output.weight | 0x7ea85720 | 0x900000 |
| 160 | blk.17.attn_q.weight | 0x7f385720 | 0x620000 |
| 161 | blk.17.attn_v.weight | 0x7f9a5720 | 0x1b8000 |
| 162 | blk.17.ffn_down.weight | 0x7fb5d720 | 0x1f80000 |
| 163 | blk.17.ffn_gate.weight | 0x81add720 | 0x1810000 |
| 164 | blk.17.ffn_norm.weight | 0x832ed720 | 0x4000 |
| 165 | blk.17.ffn_up.weight | 0x832f1720 | 0x1810000 |
| 166 | blk.18.attn_k.weight | 0x84b01720 | 0x1b8000 |
| 167 | blk.18.attn_norm.weight | 0x84cb9720 | 0x4000 |
| 168 | blk.18.attn_output.weight | 0x84cbd720 | 0x900000 |
| 169 | blk.18.attn_q.weight | 0x855bd720 | 0x6e0000 |
| 170 | blk.18.attn_v.weight | 0x85c9d720 | 0x240000 |
| 171 | blk.18.ffn_down.weight | 0x85edd720 | 0x1f80000 |
| 172 | blk.18.ffn_gate.weight | 0x87e5d720 | 0x1810000 |
| 173 | blk.18.ffn_norm.weight | 0x8966d720 | 0x4000 |
| 174 | blk.18.ffn_up.weight | 0x89671720 | 0x1810000 |
| 175 | blk.19.attn_k.weight | 0x8ae81720 | 0x1b8000 |
| 176 | blk.19.attn_norm.weight | 0x8b039720 | 0x4000 |
| 177 | blk.19.attn_output.weight | 0x8b03d720 | 0x900000 |
| 178 | blk.19.attn_q.weight | 0x8b93d720 | 0x6e0000 |
| 179 | blk.19.attn_v.weight | 0x8c01d720 | 0x240000 |
| 180 | blk.19.ffn_down.weight | 0x8c25d720 | 0x1f80000 |
| 181 | blk.19.ffn_gate.weight | 0x8e1dd720 | 0x1810000 |
| 182 | blk.19.ffn_norm.weight | 0x8f9ed720 | 0x4000 |
| 183 | blk.19.ffn_up.weight | 0x8f9f1720 | 0x1810000 |
| 184 | blk.20.attn_k.weight | 0x91201720 | 0x1b8000 |
| 185 | blk.20.attn_norm.weight | 0x913b9720 | 0x4000 |
| 186 | blk.20.attn_output.weight | 0x913bd720 | 0x900000 |
| 187 | blk.20.attn_q.weight | 0x91cbd720 | 0x6e0000 |
| 188 | blk.20.attn_v.weight | 0x9239d720 | 0x240000 |
| 189 | blk.20.ffn_down.weight | 0x925dd720 | 0x1f80000 |
| 190 | blk.20.ffn_gate.weight | 0x9455d720 | 0x1810000 |
| 191 | blk.20.ffn_norm.weight | 0x95d6d720 | 0x4000 |
| 192 | blk.20.ffn_up.weight | 0x95d71720 | 0x1810000 |
| 193 | blk.21.attn_k.weight | 0x97581720 | 0x1b8000 |
| 194 | blk.21.attn_norm.weight | 0x97739720 | 0x4000 |
| 195 | blk.21.attn_output.weight | 0x9773d720 | 0x900000 |
| 196 | blk.21.attn_q.weight | 0x9803d720 | 0x6e0000 |
| 197 | blk.21.attn_v.weight | 0x9871d720 | 0x240000 |
| 198 | blk.21.ffn_down.weight | 0x9895d720 | 0x1f80000 |
| 199 | blk.21.ffn_gate.weight | 0x9a8dd720 | 0x1810000 |
| 200 | blk.21.ffn_norm.weight | 0x9c0ed720 | 0x4000 |
| 201 | blk.21.ffn_up.weight | 0x9c0f1720 | 0x1810000 |
| 202 | blk.22.attn_k.weight | 0x9d901720 | 0x1b8000 |
| 203 | blk.22.attn_norm.weight | 0x9dab9720 | 0x4000 |
| 204 | blk.22.attn_output.weight | 0x9dabd720 | 0x900000 |
| 205 | blk.22.attn_q.weight | 0x9e3bd720 | 0x6e0000 |
| 206 | blk.22.attn_v.weight | 0x9ea9d720 | 0x240000 |
| 207 | blk.22.ffn_down.weight | 0x9ecdd720 | 0x1f80000 |
| 208 | blk.22.ffn_gate.weight | 0xa0c5d720 | 0x1810000 |
| 209 | blk.22.ffn_norm.weight | 0xa246d720 | 0x4000 |
| 210 | blk.22.ffn_up.weight | 0xa2471720 | 0x1810000 |
| 211 | blk.23.attn_k.weight | 0xa3c81720 | 0x1b8000 |
| 212 | blk.23.attn_norm.weight | 0xa3e39720 | 0x4000 |
| 213 | blk.23.attn_output.weight | 0xa3e3d720 | 0x900000 |
| 214 | blk.23.attn_q.weight | 0xa473d720 | 0x6e0000 |
| 215 | blk.23.attn_v.weight | 0xa4e1d720 | 0x240000 |
| 216 | blk.23.ffn_down.weight | 0xa505d720 | 0x1f80000 |
| 217 | blk.23.ffn_gate.weight | 0xa6fdd720 | 0x1810000 |
| 218 | blk.23.ffn_norm.weight | 0xa87ed720 | 0x4000 |
| 219 | blk.23.ffn_up.weight | 0xa87f1720 | 0x1810000 |
| 220 | blk.24.attn_k.weight | 0xaa001720 | 0x1b8000 |
| 221 | blk.24.attn_norm.weight | 0xaa1b9720 | 0x4000 |
| 222 | blk.24.attn_output.weight | 0xaa1bd720 | 0x900000 |
| 223 | blk.24.attn_q.weight | 0xaaabd720 | 0x6e0000 |
| 224 | blk.24.attn_v.weight | 0xab19d720 | 0x240000 |
| 225 | blk.24.ffn_down.weight | 0xab3dd720 | 0x1f80000 |
| 226 | blk.24.ffn_gate.weight | 0xad35d720 | 0x1810000 |
| 227 | blk.24.ffn_norm.weight | 0xaeb6d720 | 0x4000 |
| 228 | blk.24.ffn_up.weight | 0xaeb71720 | 0x1810000 |
| 229 | blk.25.attn_k.weight | 0xb0381720 | 0x1b8000 |
| 230 | blk.25.attn_norm.weight | 0xb0539720 | 0x4000 |
| 231 | blk.25.attn_output.weight | 0xb053d720 | 0x900000 |
| 232 | blk.25.attn_q.weight | 0xb0e3d720 | 0x6e0000 |
| 233 | blk.25.attn_v.weight | 0xb151d720 | 0x240000 |
| 234 | blk.25.ffn_down.weight | 0xb175d720 | 0x1f80000 |
| 235 | blk.25.ffn_gate.weight | 0xb36dd720 | 0x1810000 |
| 236 | blk.25.ffn_norm.weight | 0xb4eed720 | 0x4000 |
| 237 | blk.25.ffn_up.weight | 0xb4ef1720 | 0x1810000 |
| 238 | blk.26.attn_k.weight | 0xb6701720 | 0x1b8000 |
| 239 | blk.26.attn_norm.weight | 0xb68b9720 | 0x4000 |
| 240 | blk.26.attn_output.weight | 0xb68bd720 | 0x900000 |
| 241 | blk.26.attn_q.weight | 0xb71bd720 | 0x6e0000 |
| 242 | blk.26.attn_v.weight | 0xb789d720 | 0x240000 |
| 243 | blk.26.ffn_down.weight | 0xb7add720 | 0x1f80000 |
| 244 | blk.26.ffn_gate.weight | 0xb9a5d720 | 0x1810000 |
| 245 | blk.26.ffn_norm.weight | 0xbb26d720 | 0x4000 |
| 246 | blk.26.ffn_up.weight | 0xbb271720 | 0x1810000 |
| 247 | blk.27.attn_k.weight | 0xbca81720 | 0x1b8000 |
| 248 | blk.27.attn_norm.weight | 0xbcc39720 | 0x4000 |
| 249 | blk.27.attn_output.weight | 0xbcc3d720 | 0x900000 |
| 250 | blk.27.attn_q.weight | 0xbd53d720 | 0x6e0000 |
| 251 | blk.27.attn_v.weight | 0xbdc1d720 | 0x240000 |
| 252 | blk.27.ffn_down.weight | 0xbde5d720 | 0x1f80000 |
| 253 | blk.27.ffn_gate.weight | 0xbfddd720 | 0x1810000 |
| 254 | blk.27.ffn_norm.weight | 0xc15ed720 | 0x4000 |
| 255 | blk.27.ffn_up.weight | 0xc15f1720 | 0x1810000 |
| 256 | blk.28.attn_k.weight | 0xc2e01720 | 0x1b8000 |
| 257 | blk.28.attn_norm.weight | 0xc2fb9720 | 0x4000 |
| 258 | blk.28.attn_output.weight | 0xc2fbd720 | 0x900000 |
| 259 | blk.28.attn_q.weight | 0xc38bd720 | 0x6e0000 |
| 260 | blk.28.attn_v.weight | 0xc3f9d720 | 0x240000 |
| 261 | blk.28.ffn_down.weight | 0xc41dd720 | 0x1f80000 |
| 262 | blk.28.ffn_gate.weight | 0xc615d720 | 0x1810000 |
| 263 | blk.28.ffn_norm.weight | 0xc796d720 | 0x4000 |
| 264 | blk.28.ffn_up.weight | 0xc7971720 | 0x1810000 |
| 265 | blk.29.attn_k.weight | 0xc9181720 | 0x1b8000 |
| 266 | blk.29.attn_norm.weight | 0xc9339720 | 0x4000 |
| 267 | blk.29.attn_output.weight | 0xc933d720 | 0x900000 |
| 268 | blk.29.attn_q.weight | 0xc9c3d720 | 0x6e0000 |
| 269 | blk.29.attn_v.weight | 0xca31d720 | 0x240000 |
| 270 | blk.29.ffn_down.weight | 0xca55d720 | 0x1f80000 |
| 271 | blk.29.ffn_gate.weight | 0xcc4dd720 | 0x1810000 |
| 272 | blk.29.ffn_norm.weight | 0xcdced720 | 0x4000 |
| 273 | blk.29.ffn_up.weight | 0xcdcf1720 | 0x1810000 |
| 274 | blk.30.attn_k.weight | 0xcf501720 | 0x1b8000 |
| 275 | blk.30.attn_norm.weight | 0xcf6b9720 | 0x4000 |
| 276 | blk.30.attn_output.weight | 0xcf6bd720 | 0x900000 |
| 277 | blk.30.attn_q.weight | 0xcffbd720 | 0x6e0000 |
| 278 | blk.30.attn_v.weight | 0xd069d720 | 0x240000 |
| 279 | blk.30.ffn_down.weight | 0xd08dd720 | 0x1f80000 |
| 280 | blk.30.ffn_gate.weight | 0xd285d720 | 0x1810000 |
| 281 | blk.30.ffn_norm.weight | 0xd406d720 | 0x4000 |
| 282 | blk.30.ffn_up.weight | 0xd4071720 | 0x1810000 |
| 283 | blk.31.attn_k.weight | 0xd5881720 | 0x188000 |
| 284 | blk.31.attn_norm.weight | 0xd5a09720 | 0x4000 |
| 285 | blk.31.attn_output.weight | 0xd5a0d720 | 0x900000 |
| 286 | blk.31.attn_q.weight | 0xd630d720 | 0x620000 |
| 287 | blk.31.attn_v.weight | 0xd692d720 | 0x1b8000 |
| 288 | blk.31.ffn_down.weight | 0xd6ae5720 | 0x1f80000 |
| 289 | blk.31.ffn_gate.weight | 0xd8a65720 | 0x1810000 |
| 290 | blk.31.ffn_norm.weight | 0xda275720 | 0x4000 |
| 291 | blk.31.ffn_up.weight | 0xda279720 | 0x1810000 |
### <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) | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ3_S |
| 1 | output_norm.weight | Output Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 2 | rope_freqs.weight | Rope_Freqs (W) | ( 64) 64 | 64 x 1 x 1 x 1 | F32 |
| 3 | token_embd.weight | Token Embedding (W) | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ3_S |
- Total elements in base: ( ~1B) 1050677312
- Percentage of total elements: 13.08%
### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
| 4 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 5 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 6 | blk.0.attn_output.weight | Block 0 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 7 | blk.0.attn_q.weight | Block 0 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 8 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 9 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 10 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 11 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 12 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.0: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
| 13 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 14 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 15 | blk.1.attn_output.weight | Block 1 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 16 | blk.1.attn_q.weight | Block 1 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 17 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 18 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 19 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 20 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 21 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.1: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
| 22 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 23 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 24 | blk.2.attn_output.weight | Block 2 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 25 | blk.2.attn_q.weight | Block 2 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 26 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 27 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 28 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 29 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 30 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.2: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
| 31 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 32 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 33 | blk.3.attn_output.weight | Block 3 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 34 | blk.3.attn_q.weight | Block 3 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 35 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 36 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 37 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 38 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 39 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.3: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
| 40 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 41 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 42 | blk.4.attn_output.weight | Block 4 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 43 | blk.4.attn_q.weight | Block 4 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 44 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 45 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 46 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 47 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 48 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.4: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
| 49 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 50 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 51 | blk.5.attn_output.weight | Block 5 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 52 | blk.5.attn_q.weight | Block 5 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 53 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 54 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 55 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 56 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 57 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.5: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
| 58 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 59 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 60 | blk.6.attn_output.weight | Block 6 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 61 | blk.6.attn_q.weight | Block 6 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 62 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 63 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 64 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 65 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 66 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.6: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
| 67 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 68 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 69 | blk.7.attn_output.weight | Block 7 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 70 | blk.7.attn_q.weight | Block 7 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 71 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 72 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 73 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 74 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 75 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.7: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
| 76 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 77 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 78 | blk.8.attn_output.weight | Block 8 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 79 | blk.8.attn_q.weight | Block 8 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 80 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 81 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 82 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 83 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 84 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.8: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
| 85 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 86 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 87 | blk.9.attn_output.weight | Block 9 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 88 | blk.9.attn_q.weight | Block 9 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 89 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 90 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 91 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 92 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 93 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.9: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
| 94 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 95 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 96 | blk.10.attn_output.weight | Block 10 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 97 | blk.10.attn_q.weight | Block 10 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 98 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 99 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 100 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 101 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 102 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.10: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
| 103 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 104 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 105 | blk.11.attn_output.weight | Block 11 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 106 | blk.11.attn_q.weight | Block 11 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 107 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 108 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 109 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 110 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 111 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.11: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
| 112 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 113 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 114 | blk.12.attn_output.weight | Block 12 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 115 | blk.12.attn_q.weight | Block 12 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 116 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 117 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 118 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 119 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 120 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.12: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
| 121 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 122 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 123 | blk.13.attn_output.weight | Block 13 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 124 | blk.13.attn_q.weight | Block 13 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 125 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 126 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 127 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 128 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 129 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.13: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
| 130 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 131 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 132 | blk.14.attn_output.weight | Block 14 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 133 | blk.14.attn_q.weight | Block 14 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 134 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 135 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 136 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 137 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 138 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.14: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
| 139 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 140 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 141 | blk.15.attn_output.weight | Block 15 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 142 | blk.15.attn_q.weight | Block 15 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 143 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 144 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 145 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
| 146 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 147 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_XXS |
- Total elements in blk.15: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 148 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 149 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 150 | blk.16.attn_output.weight | Block 16 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 151 | blk.16.attn_q.weight | Block 16 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 152 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 153 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 154 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 155 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 156 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.16: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
| 157 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 158 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 159 | blk.17.attn_output.weight | Block 17 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 160 | blk.17.attn_q.weight | Block 17 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 161 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 162 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 163 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 164 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 165 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.17: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 166 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 167 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 168 | blk.18.attn_output.weight | Block 18 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 169 | blk.18.attn_q.weight | Block 18 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 170 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 171 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 172 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 173 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 174 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.18: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 175 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 176 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 177 | blk.19.attn_output.weight | Block 19 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 178 | blk.19.attn_q.weight | Block 19 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 179 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 180 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 181 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 182 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 183 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.19: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 184 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 185 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 186 | blk.20.attn_output.weight | Block 20 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 187 | blk.20.attn_q.weight | Block 20 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 188 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 189 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 190 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 191 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 192 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.20: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 193 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 194 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 195 | blk.21.attn_output.weight | Block 21 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 196 | blk.21.attn_q.weight | Block 21 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 197 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 198 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 199 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 200 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 201 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.21: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 202 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 203 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 204 | blk.22.attn_output.weight | Block 22 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 205 | blk.22.attn_q.weight | Block 22 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 206 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 207 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 208 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 209 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 210 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.22: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 211 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 212 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 213 | blk.23.attn_output.weight | Block 23 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 214 | blk.23.attn_q.weight | Block 23 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 215 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 216 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 217 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 218 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 219 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.23: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 220 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 221 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 222 | blk.24.attn_output.weight | Block 24 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 223 | blk.24.attn_q.weight | Block 24 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 224 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 225 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 226 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 227 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 228 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.24: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 229 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 230 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 231 | blk.25.attn_output.weight | Block 25 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 232 | blk.25.attn_q.weight | Block 25 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 233 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 234 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 235 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 236 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 237 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.25: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 238 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 239 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 240 | blk.26.attn_output.weight | Block 26 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 241 | blk.26.attn_q.weight | Block 26 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 242 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 243 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 244 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 245 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 246 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.26: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 247 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 248 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 249 | blk.27.attn_output.weight | Block 27 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 250 | blk.27.attn_q.weight | Block 27 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 251 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 252 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 253 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 254 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 255 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.27: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 256 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 257 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 258 | blk.28.attn_output.weight | Block 28 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 259 | blk.28.attn_q.weight | Block 28 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 260 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 261 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 262 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 263 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 264 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.28: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 265 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 266 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 267 | blk.29.attn_output.weight | Block 29 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 268 | blk.29.attn_q.weight | Block 29 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 269 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 270 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 271 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 272 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 273 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.29: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
| 274 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 275 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 276 | blk.30.attn_output.weight | Block 30 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 277 | blk.30.attn_q.weight | Block 30 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 278 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 279 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 280 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 281 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 282 | blk.30.ffn_up.weight | Block 30 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.30: (~218M) 218112000
- Percentage of total elements: 2.72%
### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
| 283 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_XXS |
| 284 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 285 | blk.31.attn_output.weight | Block 31 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q4_K |
| 286 | blk.31.attn_q.weight | Block 31 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_XXS |
| 287 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 288 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | IQ4_NL |
| 289 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 290 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 291 | blk.31.ffn_up.weight | Block 31 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.31: (~218M) 218112000
- Percentage of total elements: 2.72%
Reference in New Issue View Git Blame Copy Permalink