# Watt-Tool-8B-Q6_K.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 | 18 |
| 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-Q6\_K.gguf - GGUF Internal File Dump](#watt-tool-8b-q6_kgguf---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 | 0x19afa000 |
| 1 | output_norm.weight | 0x1a273620 | 0x4000 |
| 2 | rope_freqs.weight | 0x1a277620 | 0x100 |
| 3 | token_embd.weight | 0x1a277720 | 0xd746000 |
| 4 | blk.0.attn_k.weight | 0x279bd720 | 0x2c0000 |
| 5 | blk.0.attn_norm.weight | 0x27c7d720 | 0x4000 |
| 6 | blk.0.attn_output.weight | 0x27c81720 | 0xd20000 |
| 7 | blk.0.attn_q.weight | 0x289a1720 | 0xb00000 |
| 8 | blk.0.attn_v.weight | 0x294a1720 | 0x348000 |
| 9 | blk.0.ffn_down.weight | 0x297e9720 | 0x3b80000 |
| 10 | blk.0.ffn_gate.weight | 0x2d369720 | 0x2680000 |
| 11 | blk.0.ffn_norm.weight | 0x2f9e9720 | 0x4000 |
| 12 | blk.0.ffn_up.weight | 0x2f9ed720 | 0x2680000 |
| 13 | blk.1.attn_k.weight | 0x3206d720 | 0x2c0000 |
| 14 | blk.1.attn_norm.weight | 0x3232d720 | 0x4000 |
| 15 | blk.1.attn_output.weight | 0x32331720 | 0xd20000 |
| 16 | blk.1.attn_q.weight | 0x33051720 | 0xb00000 |
| 17 | blk.1.attn_v.weight | 0x33b51720 | 0x348000 |
| 18 | blk.1.ffn_down.weight | 0x33e99720 | 0x3b80000 |
| 19 | blk.1.ffn_gate.weight | 0x37a19720 | 0x2680000 |
| 20 | blk.1.ffn_norm.weight | 0x3a099720 | 0x4000 |
| 21 | blk.1.ffn_up.weight | 0x3a09d720 | 0x2680000 |
| 22 | blk.2.attn_k.weight | 0x3c71d720 | 0x2c0000 |
| 23 | blk.2.attn_norm.weight | 0x3c9dd720 | 0x4000 |
| 24 | blk.2.attn_output.weight | 0x3c9e1720 | 0xd20000 |
| 25 | blk.2.attn_q.weight | 0x3d701720 | 0xb00000 |
| 26 | blk.2.attn_v.weight | 0x3e201720 | 0x348000 |
| 27 | blk.2.ffn_down.weight | 0x3e549720 | 0x3b80000 |
| 28 | blk.2.ffn_gate.weight | 0x420c9720 | 0x2680000 |
| 29 | blk.2.ffn_norm.weight | 0x44749720 | 0x4000 |
| 30 | blk.2.ffn_up.weight | 0x4474d720 | 0x2680000 |
| 31 | blk.3.attn_k.weight | 0x46dcd720 | 0x2c0000 |
| 32 | blk.3.attn_norm.weight | 0x4708d720 | 0x4000 |
| 33 | blk.3.attn_output.weight | 0x47091720 | 0xd20000 |
| 34 | blk.3.attn_q.weight | 0x47db1720 | 0xb00000 |
| 35 | blk.3.attn_v.weight | 0x488b1720 | 0x348000 |
| 36 | blk.3.ffn_down.weight | 0x48bf9720 | 0x3b80000 |
| 37 | blk.3.ffn_gate.weight | 0x4c779720 | 0x2680000 |
| 38 | blk.3.ffn_norm.weight | 0x4edf9720 | 0x4000 |
| 39 | blk.3.ffn_up.weight | 0x4edfd720 | 0x2680000 |
| 40 | blk.4.attn_k.weight | 0x5147d720 | 0x2c0000 |
| 41 | blk.4.attn_norm.weight | 0x5173d720 | 0x4000 |
| 42 | blk.4.attn_output.weight | 0x51741720 | 0xd20000 |
| 43 | blk.4.attn_q.weight | 0x52461720 | 0xb00000 |
| 44 | blk.4.attn_v.weight | 0x52f61720 | 0x348000 |
| 45 | blk.4.ffn_down.weight | 0x532a9720 | 0x3b80000 |
| 46 | blk.4.ffn_gate.weight | 0x56e29720 | 0x2680000 |
| 47 | blk.4.ffn_norm.weight | 0x594a9720 | 0x4000 |
| 48 | blk.4.ffn_up.weight | 0x594ad720 | 0x2680000 |
| 49 | blk.5.attn_k.weight | 0x5bb2d720 | 0x2c0000 |
| 50 | blk.5.attn_norm.weight | 0x5bded720 | 0x4000 |
| 51 | blk.5.attn_output.weight | 0x5bdf1720 | 0xd20000 |
| 52 | blk.5.attn_q.weight | 0x5cb11720 | 0xb00000 |
| 53 | blk.5.attn_v.weight | 0x5d611720 | 0x348000 |
| 54 | blk.5.ffn_down.weight | 0x5d959720 | 0x3b80000 |
| 55 | blk.5.ffn_gate.weight | 0x614d9720 | 0x2680000 |
| 56 | blk.5.ffn_norm.weight | 0x63b59720 | 0x4000 |
| 57 | blk.5.ffn_up.weight | 0x63b5d720 | 0x2680000 |
| 58 | blk.6.attn_k.weight | 0x661dd720 | 0x2c0000 |
| 59 | blk.6.attn_norm.weight | 0x6649d720 | 0x4000 |
| 60 | blk.6.attn_output.weight | 0x664a1720 | 0xd20000 |
| 61 | blk.6.attn_q.weight | 0x671c1720 | 0xb00000 |
| 62 | blk.6.attn_v.weight | 0x67cc1720 | 0x348000 |
| 63 | blk.6.ffn_down.weight | 0x68009720 | 0x3b80000 |
| 64 | blk.6.ffn_gate.weight | 0x6bb89720 | 0x2680000 |
| 65 | blk.6.ffn_norm.weight | 0x6e209720 | 0x4000 |
| 66 | blk.6.ffn_up.weight | 0x6e20d720 | 0x2680000 |
| 67 | blk.7.attn_k.weight | 0x7088d720 | 0x2c0000 |
| 68 | blk.7.attn_norm.weight | 0x70b4d720 | 0x4000 |
| 69 | blk.7.attn_output.weight | 0x70b51720 | 0xd20000 |
| 70 | blk.7.attn_q.weight | 0x71871720 | 0xb00000 |
| 71 | blk.7.attn_v.weight | 0x72371720 | 0x348000 |
| 72 | blk.7.ffn_down.weight | 0x726b9720 | 0x3b80000 |
| 73 | blk.7.ffn_gate.weight | 0x76239720 | 0x2680000 |
| 74 | blk.7.ffn_norm.weight | 0x788b9720 | 0x4000 |
| 75 | blk.7.ffn_up.weight | 0x788bd720 | 0x2680000 |
| 76 | blk.8.attn_k.weight | 0x7af3d720 | 0x2c0000 |
| 77 | blk.8.attn_norm.weight | 0x7b1fd720 | 0x4000 |
| 78 | blk.8.attn_output.weight | 0x7b201720 | 0xd20000 |
| 79 | blk.8.attn_q.weight | 0x7bf21720 | 0xb00000 |
| 80 | blk.8.attn_v.weight | 0x7ca21720 | 0x348000 |
| 81 | blk.8.ffn_down.weight | 0x7cd69720 | 0x3b80000 |
| 82 | blk.8.ffn_gate.weight | 0x808e9720 | 0x2680000 |
| 83 | blk.8.ffn_norm.weight | 0x82f69720 | 0x4000 |
| 84 | blk.8.ffn_up.weight | 0x82f6d720 | 0x2680000 |
| 85 | blk.9.attn_k.weight | 0x855ed720 | 0x2c0000 |
| 86 | blk.9.attn_norm.weight | 0x858ad720 | 0x4000 |
| 87 | blk.9.attn_output.weight | 0x858b1720 | 0xd20000 |
| 88 | blk.9.attn_q.weight | 0x865d1720 | 0xb00000 |
| 89 | blk.9.attn_v.weight | 0x870d1720 | 0x348000 |
| 90 | blk.9.ffn_down.weight | 0x87419720 | 0x3b80000 |
| 91 | blk.9.ffn_gate.weight | 0x8af99720 | 0x2680000 |
| 92 | blk.9.ffn_norm.weight | 0x8d619720 | 0x4000 |
| 93 | blk.9.ffn_up.weight | 0x8d61d720 | 0x2680000 |
| 94 | blk.10.attn_k.weight | 0x8fc9d720 | 0x2c0000 |
| 95 | blk.10.attn_norm.weight | 0x8ff5d720 | 0x4000 |
| 96 | blk.10.attn_output.weight | 0x8ff61720 | 0xd20000 |
| 97 | blk.10.attn_q.weight | 0x90c81720 | 0xb00000 |
| 98 | blk.10.attn_v.weight | 0x91781720 | 0x348000 |
| 99 | blk.10.ffn_down.weight | 0x91ac9720 | 0x3b80000 |
| 100 | blk.10.ffn_gate.weight | 0x95649720 | 0x2680000 |
| 101 | blk.10.ffn_norm.weight | 0x97cc9720 | 0x4000 |
| 102 | blk.10.ffn_up.weight | 0x97ccd720 | 0x2680000 |
| 103 | blk.11.attn_k.weight | 0x9a34d720 | 0x2c0000 |
| 104 | blk.11.attn_norm.weight | 0x9a60d720 | 0x4000 |
| 105 | blk.11.attn_output.weight | 0x9a611720 | 0xd20000 |
| 106 | blk.11.attn_q.weight | 0x9b331720 | 0xb00000 |
| 107 | blk.11.attn_v.weight | 0x9be31720 | 0x348000 |
| 108 | blk.11.ffn_down.weight | 0x9c179720 | 0x3b80000 |
| 109 | blk.11.ffn_gate.weight | 0x9fcf9720 | 0x2680000 |
| 110 | blk.11.ffn_norm.weight | 0xa2379720 | 0x4000 |
| 111 | blk.11.ffn_up.weight | 0xa237d720 | 0x2680000 |
| 112 | blk.12.attn_k.weight | 0xa49fd720 | 0x2c0000 |
| 113 | blk.12.attn_norm.weight | 0xa4cbd720 | 0x4000 |
| 114 | blk.12.attn_output.weight | 0xa4cc1720 | 0xd20000 |
| 115 | blk.12.attn_q.weight | 0xa59e1720 | 0xb00000 |
| 116 | blk.12.attn_v.weight | 0xa64e1720 | 0x348000 |
| 117 | blk.12.ffn_down.weight | 0xa6829720 | 0x3b80000 |
| 118 | blk.12.ffn_gate.weight | 0xaa3a9720 | 0x2680000 |
| 119 | blk.12.ffn_norm.weight | 0xaca29720 | 0x4000 |
| 120 | blk.12.ffn_up.weight | 0xaca2d720 | 0x2680000 |
| 121 | blk.13.attn_k.weight | 0xaf0ad720 | 0x348000 |
| 122 | blk.13.attn_norm.weight | 0xaf3f5720 | 0x4000 |
| 123 | blk.13.attn_output.weight | 0xaf3f9720 | 0xd20000 |
| 124 | blk.13.attn_q.weight | 0xb0119720 | 0xd20000 |
| 125 | blk.13.attn_v.weight | 0xb0e39720 | 0x440000 |
| 126 | blk.13.ffn_down.weight | 0xb1279720 | 0x3b80000 |
| 127 | blk.13.ffn_gate.weight | 0xb4df9720 | 0x2680000 |
| 128 | blk.13.ffn_norm.weight | 0xb7479720 | 0x4000 |
| 129 | blk.13.ffn_up.weight | 0xb747d720 | 0x2680000 |
| 130 | blk.14.attn_k.weight | 0xb9afd720 | 0x348000 |
| 131 | blk.14.attn_norm.weight | 0xb9e45720 | 0x4000 |
| 132 | blk.14.attn_output.weight | 0xb9e49720 | 0xd20000 |
| 133 | blk.14.attn_q.weight | 0xbab69720 | 0xd20000 |
| 134 | blk.14.attn_v.weight | 0xbb889720 | 0x440000 |
| 135 | blk.14.ffn_down.weight | 0xbbcc9720 | 0x3b80000 |
| 136 | blk.14.ffn_gate.weight | 0xbf849720 | 0x2680000 |
| 137 | blk.14.ffn_norm.weight | 0xc1ec9720 | 0x4000 |
| 138 | blk.14.ffn_up.weight | 0xc1ecd720 | 0x2680000 |
| 139 | blk.15.attn_k.weight | 0xc454d720 | 0x2c0000 |
| 140 | blk.15.attn_norm.weight | 0xc480d720 | 0x4000 |
| 141 | blk.15.attn_output.weight | 0xc4811720 | 0xd20000 |
| 142 | blk.15.attn_q.weight | 0xc5531720 | 0xb00000 |
| 143 | blk.15.attn_v.weight | 0xc6031720 | 0x348000 |
| 144 | blk.15.ffn_down.weight | 0xc6379720 | 0x3b80000 |
| 145 | blk.15.ffn_gate.weight | 0xc9ef9720 | 0x2680000 |
| 146 | blk.15.ffn_norm.weight | 0xcc579720 | 0x4000 |
| 147 | blk.15.ffn_up.weight | 0xcc57d720 | 0x2680000 |
| 148 | blk.16.attn_k.weight | 0xcebfd720 | 0x348000 |
| 149 | blk.16.attn_norm.weight | 0xcef45720 | 0x4000 |
| 150 | blk.16.attn_output.weight | 0xcef49720 | 0xd20000 |
| 151 | blk.16.attn_q.weight | 0xcfc69720 | 0xd20000 |
| 152 | blk.16.attn_v.weight | 0xd0989720 | 0x440000 |
| 153 | blk.16.ffn_down.weight | 0xd0dc9720 | 0x3b80000 |
| 154 | blk.16.ffn_gate.weight | 0xd4949720 | 0x2df0000 |
| 155 | blk.16.ffn_norm.weight | 0xd7739720 | 0x4000 |
| 156 | blk.16.ffn_up.weight | 0xd773d720 | 0x2df0000 |
| 157 | blk.17.attn_k.weight | 0xda52d720 | 0x2c0000 |
| 158 | blk.17.attn_norm.weight | 0xda7ed720 | 0x4000 |
| 159 | blk.17.attn_output.weight | 0xda7f1720 | 0xd20000 |
| 160 | blk.17.attn_q.weight | 0xdb511720 | 0xb00000 |
| 161 | blk.17.attn_v.weight | 0xdc011720 | 0x348000 |
| 162 | blk.17.ffn_down.weight | 0xdc359720 | 0x3b80000 |
| 163 | blk.17.ffn_gate.weight | 0xdfed9720 | 0x2df0000 |
| 164 | blk.17.ffn_norm.weight | 0xe2cc9720 | 0x4000 |
| 165 | blk.17.ffn_up.weight | 0xe2ccd720 | 0x2df0000 |
| 166 | blk.18.attn_k.weight | 0xe5abd720 | 0x348000 |
| 167 | blk.18.attn_norm.weight | 0xe5e05720 | 0x4000 |
| 168 | blk.18.attn_output.weight | 0xe5e09720 | 0xd20000 |
| 169 | blk.18.attn_q.weight | 0xe6b29720 | 0xd20000 |
| 170 | blk.18.attn_v.weight | 0xe7849720 | 0x440000 |
| 171 | blk.18.ffn_down.weight | 0xe7c89720 | 0x3b80000 |
| 172 | blk.18.ffn_gate.weight | 0xeb809720 | 0x2df0000 |
| 173 | blk.18.ffn_norm.weight | 0xee5f9720 | 0x4000 |
| 174 | blk.18.ffn_up.weight | 0xee5fd720 | 0x2df0000 |
| 175 | blk.19.attn_k.weight | 0xf13ed720 | 0x348000 |
| 176 | blk.19.attn_norm.weight | 0xf1735720 | 0x4000 |
| 177 | blk.19.attn_output.weight | 0xf1739720 | 0xd20000 |
| 178 | blk.19.attn_q.weight | 0xf2459720 | 0xd20000 |
| 179 | blk.19.attn_v.weight | 0xf3179720 | 0x440000 |
| 180 | blk.19.ffn_down.weight | 0xf35b9720 | 0x3b80000 |
| 181 | blk.19.ffn_gate.weight | 0xf7139720 | 0x2df0000 |
| 182 | blk.19.ffn_norm.weight | 0xf9f29720 | 0x4000 |
| 183 | blk.19.ffn_up.weight | 0xf9f2d720 | 0x2df0000 |
| 184 | blk.20.attn_k.weight | 0xfcd1d720 | 0x348000 |
| 185 | blk.20.attn_norm.weight | 0xfd065720 | 0x4000 |
| 186 | blk.20.attn_output.weight | 0xfd069720 | 0xd20000 |
| 187 | blk.20.attn_q.weight | 0xfdd89720 | 0xd20000 |
| 188 | blk.20.attn_v.weight | 0xfeaa9720 | 0x440000 |
| 189 | blk.20.ffn_down.weight | 0xfeee9720 | 0x3b80000 |
| 190 | blk.20.ffn_gate.weight | 0x102a69720 | 0x2df0000 |
| 191 | blk.20.ffn_norm.weight | 0x105859720 | 0x4000 |
| 192 | blk.20.ffn_up.weight | 0x10585d720 | 0x2df0000 |
| 193 | blk.21.attn_k.weight | 0x10864d720 | 0x348000 |
| 194 | blk.21.attn_norm.weight | 0x108995720 | 0x4000 |
| 195 | blk.21.attn_output.weight | 0x108999720 | 0xd20000 |
| 196 | blk.21.attn_q.weight | 0x1096b9720 | 0xd20000 |
| 197 | blk.21.attn_v.weight | 0x10a3d9720 | 0x440000 |
| 198 | blk.21.ffn_down.weight | 0x10a819720 | 0x3b80000 |
| 199 | blk.21.ffn_gate.weight | 0x10e399720 | 0x2df0000 |
| 200 | blk.21.ffn_norm.weight | 0x111189720 | 0x4000 |
| 201 | blk.21.ffn_up.weight | 0x11118d720 | 0x2df0000 |
| 202 | blk.22.attn_k.weight | 0x113f7d720 | 0x348000 |
| 203 | blk.22.attn_norm.weight | 0x1142c5720 | 0x4000 |
| 204 | blk.22.attn_output.weight | 0x1142c9720 | 0xd20000 |
| 205 | blk.22.attn_q.weight | 0x114fe9720 | 0xd20000 |
| 206 | blk.22.attn_v.weight | 0x115d09720 | 0x440000 |
| 207 | blk.22.ffn_down.weight | 0x116149720 | 0x3b80000 |
| 208 | blk.22.ffn_gate.weight | 0x119cc9720 | 0x2df0000 |
| 209 | blk.22.ffn_norm.weight | 0x11cab9720 | 0x4000 |
| 210 | blk.22.ffn_up.weight | 0x11cabd720 | 0x2df0000 |
| 211 | blk.23.attn_k.weight | 0x11f8ad720 | 0x348000 |
| 212 | blk.23.attn_norm.weight | 0x11fbf5720 | 0x4000 |
| 213 | blk.23.attn_output.weight | 0x11fbf9720 | 0xd20000 |
| 214 | blk.23.attn_q.weight | 0x120919720 | 0xd20000 |
| 215 | blk.23.attn_v.weight | 0x121639720 | 0x440000 |
| 216 | blk.23.ffn_down.weight | 0x121a79720 | 0x3b80000 |
| 217 | blk.23.ffn_gate.weight | 0x1255f9720 | 0x2df0000 |
| 218 | blk.23.ffn_norm.weight | 0x1283e9720 | 0x4000 |
| 219 | blk.23.ffn_up.weight | 0x1283ed720 | 0x2df0000 |
| 220 | blk.24.attn_k.weight | 0x12b1dd720 | 0x348000 |
| 221 | blk.24.attn_norm.weight | 0x12b525720 | 0x4000 |
| 222 | blk.24.attn_output.weight | 0x12b529720 | 0xd20000 |
| 223 | blk.24.attn_q.weight | 0x12c249720 | 0xd20000 |
| 224 | blk.24.attn_v.weight | 0x12cf69720 | 0x440000 |
| 225 | blk.24.ffn_down.weight | 0x12d3a9720 | 0x3b80000 |
| 226 | blk.24.ffn_gate.weight | 0x130f29720 | 0x2df0000 |
| 227 | blk.24.ffn_norm.weight | 0x133d19720 | 0x4000 |
| 228 | blk.24.ffn_up.weight | 0x133d1d720 | 0x2df0000 |
| 229 | blk.25.attn_k.weight | 0x136b0d720 | 0x348000 |
| 230 | blk.25.attn_norm.weight | 0x136e55720 | 0x4000 |
| 231 | blk.25.attn_output.weight | 0x136e59720 | 0xd20000 |
| 232 | blk.25.attn_q.weight | 0x137b79720 | 0xd20000 |
| 233 | blk.25.attn_v.weight | 0x138899720 | 0x440000 |
| 234 | blk.25.ffn_down.weight | 0x138cd9720 | 0x3b80000 |
| 235 | blk.25.ffn_gate.weight | 0x13c859720 | 0x2df0000 |
| 236 | blk.25.ffn_norm.weight | 0x13f649720 | 0x4000 |
| 237 | blk.25.ffn_up.weight | 0x13f64d720 | 0x2df0000 |
| 238 | blk.26.attn_k.weight | 0x14243d720 | 0x348000 |
| 239 | blk.26.attn_norm.weight | 0x142785720 | 0x4000 |
| 240 | blk.26.attn_output.weight | 0x142789720 | 0xd20000 |
| 241 | blk.26.attn_q.weight | 0x1434a9720 | 0xd20000 |
| 242 | blk.26.attn_v.weight | 0x1441c9720 | 0x440000 |
| 243 | blk.26.ffn_down.weight | 0x144609720 | 0x3b80000 |
| 244 | blk.26.ffn_gate.weight | 0x148189720 | 0x2df0000 |
| 245 | blk.26.ffn_norm.weight | 0x14af79720 | 0x4000 |
| 246 | blk.26.ffn_up.weight | 0x14af7d720 | 0x2df0000 |
| 247 | blk.27.attn_k.weight | 0x14dd6d720 | 0x348000 |
| 248 | blk.27.attn_norm.weight | 0x14e0b5720 | 0x4000 |
| 249 | blk.27.attn_output.weight | 0x14e0b9720 | 0xd20000 |
| 250 | blk.27.attn_q.weight | 0x14edd9720 | 0xd20000 |
| 251 | blk.27.attn_v.weight | 0x14faf9720 | 0x440000 |
| 252 | blk.27.ffn_down.weight | 0x14ff39720 | 0x3b80000 |
| 253 | blk.27.ffn_gate.weight | 0x153ab9720 | 0x2df0000 |
| 254 | blk.27.ffn_norm.weight | 0x1568a9720 | 0x4000 |
| 255 | blk.27.ffn_up.weight | 0x1568ad720 | 0x2df0000 |
| 256 | blk.28.attn_k.weight | 0x15969d720 | 0x348000 |
| 257 | blk.28.attn_norm.weight | 0x1599e5720 | 0x4000 |
| 258 | blk.28.attn_output.weight | 0x1599e9720 | 0xd20000 |
| 259 | blk.28.attn_q.weight | 0x15a709720 | 0xd20000 |
| 260 | blk.28.attn_v.weight | 0x15b429720 | 0x440000 |
| 261 | blk.28.ffn_down.weight | 0x15b869720 | 0x3b80000 |
| 262 | blk.28.ffn_gate.weight | 0x15f3e9720 | 0x2df0000 |
| 263 | blk.28.ffn_norm.weight | 0x1621d9720 | 0x4000 |
| 264 | blk.28.ffn_up.weight | 0x1621dd720 | 0x2df0000 |
| 265 | blk.29.attn_k.weight | 0x164fcd720 | 0x348000 |
| 266 | blk.29.attn_norm.weight | 0x165315720 | 0x4000 |
| 267 | blk.29.attn_output.weight | 0x165319720 | 0xd20000 |
| 268 | blk.29.attn_q.weight | 0x166039720 | 0xd20000 |
| 269 | blk.29.attn_v.weight | 0x166d59720 | 0x440000 |
| 270 | blk.29.ffn_down.weight | 0x167199720 | 0x3b80000 |
| 271 | blk.29.ffn_gate.weight | 0x16ad19720 | 0x2df0000 |
| 272 | blk.29.ffn_norm.weight | 0x16db09720 | 0x4000 |
| 273 | blk.29.ffn_up.weight | 0x16db0d720 | 0x2df0000 |
| 274 | blk.30.attn_k.weight | 0x1708fd720 | 0x348000 |
| 275 | blk.30.attn_norm.weight | 0x170c45720 | 0x4000 |
| 276 | blk.30.attn_output.weight | 0x170c49720 | 0xd20000 |
| 277 | blk.30.attn_q.weight | 0x171969720 | 0xd20000 |
| 278 | blk.30.attn_v.weight | 0x172689720 | 0x440000 |
| 279 | blk.30.ffn_down.weight | 0x172ac9720 | 0x3b80000 |
| 280 | blk.30.ffn_gate.weight | 0x176649720 | 0x2df0000 |
| 281 | blk.30.ffn_norm.weight | 0x179439720 | 0x4000 |
| 282 | blk.30.ffn_up.weight | 0x17943d720 | 0x2df0000 |
| 283 | blk.31.attn_k.weight | 0x17c22d720 | 0x2c0000 |
| 284 | blk.31.attn_norm.weight | 0x17c4ed720 | 0x4000 |
| 285 | blk.31.attn_output.weight | 0x17c4f1720 | 0xd20000 |
| 286 | blk.31.attn_q.weight | 0x17d211720 | 0xb00000 |
| 287 | blk.31.attn_v.weight | 0x17dd11720 | 0x348000 |
| 288 | blk.31.ffn_down.weight | 0x17e059720 | 0x3b80000 |
| 289 | blk.31.ffn_gate.weight | 0x181bd9720 | 0x2df0000 |
| 290 | blk.31.ffn_norm.weight | 0x1849c9720 | 0x4000 |
| 291 | blk.31.ffn_up.weight | 0x1849cd720 | 0x2df0000 |
### Base Tensor Group : ~1B Elements
| 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 | Q6_K |
| 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 | Q3_K |
- Total elements in base: ( ~1B) 1050677312
- Percentage of total elements: 13.08%
### Block 0 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 7 | blk.0.attn_q.weight | Block 0 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 8 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 9 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 10 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.0: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 1 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 16 | blk.1.attn_q.weight | Block 1 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 17 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 18 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 19 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.1: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 2 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 25 | blk.2.attn_q.weight | Block 2 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 26 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 27 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 28 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.2: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 3 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 34 | blk.3.attn_q.weight | Block 3 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 35 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 36 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 37 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.3: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 4 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 43 | blk.4.attn_q.weight | Block 4 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 44 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 45 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 46 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.4: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 5 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 52 | blk.5.attn_q.weight | Block 5 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 53 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 54 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 55 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.5: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 6 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 61 | blk.6.attn_q.weight | Block 6 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 62 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 63 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 64 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.6: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 7 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 70 | blk.7.attn_q.weight | Block 7 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 71 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 72 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 73 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.7: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 8 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 79 | blk.8.attn_q.weight | Block 8 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 80 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 81 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 82 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.8: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 9 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 88 | blk.9.attn_q.weight | Block 9 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 89 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 90 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 91 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.9: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 10 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 97 | blk.10.attn_q.weight | Block 10 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 98 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 99 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 100 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.10: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 11 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 106 | blk.11.attn_q.weight | Block 11 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 107 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 108 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 109 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.11: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 12 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 115 | blk.12.attn_q.weight | Block 12 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 116 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 117 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 118 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.12: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 13 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 124 | blk.13.attn_q.weight | Block 13 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 125 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 126 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 127 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.13: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 14 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 133 | blk.14.attn_q.weight | Block 14 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 134 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 135 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 136 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.14: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 15 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 142 | blk.15.attn_q.weight | Block 15 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 143 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 144 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 145 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q5_K |
| 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 | Q5_K |
- Total elements in blk.15: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 16 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 151 | blk.16.attn_q.weight | Block 16 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 152 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 153 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 154 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.16: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 17 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 160 | blk.17.attn_q.weight | Block 17 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 161 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 162 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 163 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.17: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 18 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 169 | blk.18.attn_q.weight | Block 18 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 170 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 171 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 172 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.18: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 19 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 178 | blk.19.attn_q.weight | Block 19 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 179 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 180 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 181 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.19: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 20 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 187 | blk.20.attn_q.weight | Block 20 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 188 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 189 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 190 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.20: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 21 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 196 | blk.21.attn_q.weight | Block 21 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 197 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 198 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 199 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.21: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 22 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 205 | blk.22.attn_q.weight | Block 22 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 206 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 207 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 208 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.22: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 23 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 214 | blk.23.attn_q.weight | Block 23 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 215 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 216 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 217 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.23: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 24 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 223 | blk.24.attn_q.weight | Block 24 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 224 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 225 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 226 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.24: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 25 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 232 | blk.25.attn_q.weight | Block 25 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 233 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 234 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 235 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.25: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 26 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 241 | blk.26.attn_q.weight | Block 26 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 242 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 243 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 244 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.26: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 27 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 250 | blk.27.attn_q.weight | Block 27 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 251 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 252 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 253 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.27: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 28 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 259 | blk.28.attn_q.weight | Block 28 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 260 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 261 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 262 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.28: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 29 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 268 | blk.29.attn_q.weight | Block 29 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 269 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 270 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 271 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.29: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 30 Tensor Group : ~218M Elements
| 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 | Q6_K |
| 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 | Q6_K |
| 277 | blk.30.attn_q.weight | Block 30 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q6_K |
| 278 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q8_0 |
| 279 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 280 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.30: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 31 Tensor Group : ~218M Elements
| 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 | Q5_K |
| 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 | Q6_K |
| 286 | blk.31.attn_q.weight | Block 31 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | Q5_K |
| 287 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | Q6_K |
| 288 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q8_0 |
| 289 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | Q6_K |
| 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 | Q6_K |
- Total elements in blk.31: (~218M) 218112000
- Percentage of total elements: 2.72%