90 KiB
90 KiB
Hammer2.1-7b-Q3_K_S.gguf - GGUF Internal File Dump
- Endian: LITTLE endian
Key Value Metadata Store
There are 36 key-value pairs in this file
| POS | TYPE | Count | Key | Value |
|---|---|---|---|---|
| 1 | UINT32 | 1 | GGUF.version | 3 |
| 2 | UINT64 | 1 | GGUF.tensor_count | 339 |
| 3 | UINT64 | 1 | GGUF.kv_count | 33 |
| 4 | STRING | 1 | general.architecture | qwen2 |
| 5 | STRING | 1 | general.type | model |
| 6 | STRING | 1 | general.name | Hammer2.1 7b GGUF |
| 7 | STRING | 1 | general.finetune | GGUF |
| 8 | STRING | 1 | general.basename | Hammer2.1 |
| 9 | STRING | 1 | general.size_label | 7B |
| 10 | UINT32 | 1 | qwen2.block_count | 28 |
| 11 | UINT32 | 1 | qwen2.context_length | 32768 |
| 12 | UINT32 | 1 | qwen2.embedding_length | 3584 |
| 13 | UINT32 | 1 | qwen2.feed_forward_length | 18944 |
| 14 | UINT32 | 1 | qwen2.attention.head_count | 28 |
| 15 | UINT32 | 1 | qwen2.attention.head_count_kv | 4 |
| 16 | FLOAT32 | 1 | qwen2.rope.freq_base | 1000000.0 |
| 17 | FLOAT32 | 1 | qwen2.attention.layer_norm_rms_epsilon | 1e-06 |
| 18 | STRING | 1 | qwen2.rope.scaling.type | yarn |
| 19 | FLOAT32 | 1 | qwen2.rope.scaling.factor | 4.0 |
| 20 | UINT32 | 1 | qwen2.rope.scaling.original_context_length | 32768 |
| 21 | STRING | 1 | tokenizer.ggml.model | gpt2 |
| 22 | STRING | 1 | tokenizer.ggml.pre | qwen2 |
| 23 | [STRING] | 151665 | tokenizer.ggml.tokens | [ !, ", #, $, %, ... ] |
| 24 | [INT32] | 151665 | tokenizer.ggml.token_type | [ 1, 1, 1, 1, 1, 1, 1, ... ] |
| 25 | [STRING] | 151387 | tokenizer.ggml.merges | [ Ġ Ġ, ĠĠ ĠĠ, i n, Ġ t, ĠĠĠĠ ĠĠĠĠ, ... ] |
| 26 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 151645 |
| 27 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 151643 |
| 28 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 151643 |
| 29 | BOOL | 1 | tokenizer.ggml.add_bos_token | False |
| 30 | STRING | 1 | tokenizer.chat_template | {%- set system_message = 'You ...`{- '< |
| 31 | UINT32 | 1 | general.quantization_version | 2 |
| 32 | UINT32 | 1 | general.file_type | 11 |
| 33 | STRING | 1 | quantize.imatrix.file | ./imatrix/imatrix-Hammer2.1-7b-small.dat |
| 34 | STRING | 1 | quantize.imatrix.dataset | ../../datasets/imatrix/calibration_eur_small.txt |
| 35 | INT32 | 1 | quantize.imatrix.entries_count | 197 |
| 36 | INT32 | 1 | quantize.imatrix.chunks_count | 968 |
Tensors Overview ~8B Elements
Total number of elements in all tensors: 7612756480 Elements
- Hammer2.1-7b-Q3_K_S.gguf - GGUF Internal File Dump
- Key Value Metadata Store
- Tensors Overview ~8B Elements
- Tensor Data Offset
- Base Tensor Group : ~1B Elements
- Block 0 Tensor Group : ~233M Elements
- Block 1 Tensor Group : ~233M Elements
- Block 2 Tensor Group : ~233M Elements
- Block 3 Tensor Group : ~233M Elements
- Block 4 Tensor Group : ~233M Elements
- Block 5 Tensor Group : ~233M Elements
- Block 6 Tensor Group : ~233M Elements
- Block 7 Tensor Group : ~233M Elements
- Block 8 Tensor Group : ~233M Elements
- Block 9 Tensor Group : ~233M Elements
- Block 10 Tensor Group : ~233M Elements
- Block 11 Tensor Group : ~233M Elements
- Block 12 Tensor Group : ~233M Elements
- Block 13 Tensor Group : ~233M Elements
- Block 14 Tensor Group : ~233M Elements
- Block 15 Tensor Group : ~233M Elements
- Block 16 Tensor Group : ~233M Elements
- Block 17 Tensor Group : ~233M Elements
- Block 18 Tensor Group : ~233M Elements
- Block 19 Tensor Group : ~233M Elements
- Block 20 Tensor Group : ~233M Elements
- Block 21 Tensor Group : ~233M Elements
- Block 22 Tensor Group : ~233M Elements
- Block 23 Tensor Group : ~233M Elements
- Block 24 Tensor Group : ~233M Elements
- Block 25 Tensor Group : ~233M Elements
- Block 26 Tensor Group : ~233M Elements
- Block 27 Tensor Group : ~233M 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 | 0x5ab4c0 | 0xdebe7c4 |
| 1 | output_norm.weight | 0xe469ca0 | 0x3800 |
| 2 | token_embd.weight | 0xe46d4a0 | 0xaa18718 |
| 3 | blk.0.attn_k.bias | 0x18e85bc0 | 0x800 |
| 4 | blk.0.attn_k.weight | 0x18e863c0 | 0x93000 |
| 5 | blk.0.attn_norm.weight | 0x18f193c0 | 0x3800 |
| 6 | blk.0.attn_output.weight | 0x18f1cbc0 | 0x543800 |
| 7 | blk.0.attn_q.bias | 0x194603c0 | 0x3800 |
| 8 | blk.0.attn_q.weight | 0x19463bc0 | 0x405000 |
| 9 | blk.0.attn_v.bias | 0x19868bc0 | 0x800 |
| 10 | blk.0.attn_v.weight | 0x198693c0 | 0xc0800 |
| 11 | blk.0.ffn_down.weight | 0x19929bc0 | 0x1bd2800 |
| 12 | blk.0.ffn_gate.weight | 0x1b4fc3c0 | 0x153f000 |
| 13 | blk.0.ffn_norm.weight | 0x1ca3b3c0 | 0x3800 |
| 14 | blk.0.ffn_up.weight | 0x1ca3ebc0 | 0x153f000 |
| 15 | blk.1.attn_k.bias | 0x1df7dbc0 | 0x800 |
| 16 | blk.1.attn_k.weight | 0x1df7e3c0 | 0x93000 |
| 17 | blk.1.attn_norm.weight | 0x1e0113c0 | 0x3800 |
| 18 | blk.1.attn_output.weight | 0x1e014bc0 | 0x543800 |
| 19 | blk.1.attn_q.bias | 0x1e5583c0 | 0x3800 |
| 20 | blk.1.attn_q.weight | 0x1e55bbc0 | 0x405000 |
| 21 | blk.1.attn_v.bias | 0x1e960bc0 | 0x800 |
| 22 | blk.1.attn_v.weight | 0x1e9613c0 | 0xc0800 |
| 23 | blk.1.ffn_down.weight | 0x1ea21bc0 | 0x1bd2800 |
| 24 | blk.1.ffn_gate.weight | 0x205f43c0 | 0x1bd2800 |
| 25 | blk.1.ffn_norm.weight | 0x221c6bc0 | 0x3800 |
| 26 | blk.1.ffn_up.weight | 0x221ca3c0 | 0x1bd2800 |
| 27 | blk.2.attn_k.bias | 0x23d9cbc0 | 0x800 |
| 28 | blk.2.attn_k.weight | 0x23d9d3c0 | 0x93000 |
| 29 | blk.2.attn_norm.weight | 0x23e303c0 | 0x3800 |
| 30 | blk.2.attn_output.weight | 0x23e33bc0 | 0x543800 |
| 31 | blk.2.attn_q.bias | 0x243773c0 | 0x3800 |
| 32 | blk.2.attn_q.weight | 0x2437abc0 | 0x405000 |
| 33 | blk.2.attn_v.bias | 0x2477fbc0 | 0x800 |
| 34 | blk.2.attn_v.weight | 0x247803c0 | 0xc0800 |
| 35 | blk.2.ffn_down.weight | 0x24840bc0 | 0x1bd2800 |
| 36 | blk.2.ffn_gate.weight | 0x264133c0 | 0x1bd2800 |
| 37 | blk.2.ffn_norm.weight | 0x27fe5bc0 | 0x3800 |
| 38 | blk.2.ffn_up.weight | 0x27fe93c0 | 0x1bd2800 |
| 39 | blk.3.attn_k.bias | 0x29bbbbc0 | 0x800 |
| 40 | blk.3.attn_k.weight | 0x29bbc3c0 | 0x93000 |
| 41 | blk.3.attn_norm.weight | 0x29c4f3c0 | 0x3800 |
| 42 | blk.3.attn_output.weight | 0x29c52bc0 | 0x543800 |
| 43 | blk.3.attn_q.bias | 0x2a1963c0 | 0x3800 |
| 44 | blk.3.attn_q.weight | 0x2a199bc0 | 0x405000 |
| 45 | blk.3.attn_v.bias | 0x2a59ebc0 | 0x800 |
| 46 | blk.3.attn_v.weight | 0x2a59f3c0 | 0xc0800 |
| 47 | blk.3.ffn_down.weight | 0x2a65fbc0 | 0x246c000 |
| 48 | blk.3.ffn_gate.weight | 0x2cacbbc0 | 0x1bd2800 |
| 49 | blk.3.ffn_norm.weight | 0x2e69e3c0 | 0x3800 |
| 50 | blk.3.ffn_up.weight | 0x2e6a1bc0 | 0x1bd2800 |
| 51 | blk.4.attn_k.bias | 0x302743c0 | 0x800 |
| 52 | blk.4.attn_k.weight | 0x30274bc0 | 0x93000 |
| 53 | blk.4.attn_norm.weight | 0x30307bc0 | 0x3800 |
| 54 | blk.4.attn_output.weight | 0x3030b3c0 | 0x543800 |
| 55 | blk.4.attn_q.bias | 0x3084ebc0 | 0x3800 |
| 56 | blk.4.attn_q.weight | 0x308523c0 | 0x405000 |
| 57 | blk.4.attn_v.bias | 0x30c573c0 | 0x800 |
| 58 | blk.4.attn_v.weight | 0x30c57bc0 | 0xc0800 |
| 59 | blk.4.ffn_down.weight | 0x30d183c0 | 0x1bd2800 |
| 60 | blk.4.ffn_gate.weight | 0x328eabc0 | 0x1bd2800 |
| 61 | blk.4.ffn_norm.weight | 0x344bd3c0 | 0x3800 |
| 62 | blk.4.ffn_up.weight | 0x344c0bc0 | 0x1bd2800 |
| 63 | blk.5.attn_k.bias | 0x360933c0 | 0x800 |
| 64 | blk.5.attn_k.weight | 0x36093bc0 | 0x93000 |
| 65 | blk.5.attn_norm.weight | 0x36126bc0 | 0x3800 |
| 66 | blk.5.attn_output.weight | 0x3612a3c0 | 0x543800 |
| 67 | blk.5.attn_q.bias | 0x3666dbc0 | 0x3800 |
| 68 | blk.5.attn_q.weight | 0x366713c0 | 0x405000 |
| 69 | blk.5.attn_v.bias | 0x36a763c0 | 0x800 |
| 70 | blk.5.attn_v.weight | 0x36a76bc0 | 0xc0800 |
| 71 | blk.5.ffn_down.weight | 0x36b373c0 | 0x1bd2800 |
| 72 | blk.5.ffn_gate.weight | 0x38709bc0 | 0x1bd2800 |
| 73 | blk.5.ffn_norm.weight | 0x3a2dc3c0 | 0x3800 |
| 74 | blk.5.ffn_up.weight | 0x3a2dfbc0 | 0x1bd2800 |
| 75 | blk.6.attn_k.bias | 0x3beb23c0 | 0x800 |
| 76 | blk.6.attn_k.weight | 0x3beb2bc0 | 0x93000 |
| 77 | blk.6.attn_norm.weight | 0x3bf45bc0 | 0x3800 |
| 78 | blk.6.attn_output.weight | 0x3bf493c0 | 0x543800 |
| 79 | blk.6.attn_q.bias | 0x3c48cbc0 | 0x3800 |
| 80 | blk.6.attn_q.weight | 0x3c4903c0 | 0x405000 |
| 81 | blk.6.attn_v.bias | 0x3c8953c0 | 0x800 |
| 82 | blk.6.attn_v.weight | 0x3c895bc0 | 0xc0800 |
| 83 | blk.6.ffn_down.weight | 0x3c9563c0 | 0x1bd2800 |
| 84 | blk.6.ffn_gate.weight | 0x3e528bc0 | 0x153f000 |
| 85 | blk.6.ffn_norm.weight | 0x3fa67bc0 | 0x3800 |
| 86 | blk.6.ffn_up.weight | 0x3fa6b3c0 | 0x153f000 |
| 87 | blk.7.attn_k.bias | 0x40faa3c0 | 0x800 |
| 88 | blk.7.attn_k.weight | 0x40faabc0 | 0x93000 |
| 89 | blk.7.attn_norm.weight | 0x4103dbc0 | 0x3800 |
| 90 | blk.7.attn_output.weight | 0x410413c0 | 0x543800 |
| 91 | blk.7.attn_q.bias | 0x41584bc0 | 0x3800 |
| 92 | blk.7.attn_q.weight | 0x415883c0 | 0x405000 |
| 93 | blk.7.attn_v.bias | 0x4198d3c0 | 0x800 |
| 94 | blk.7.attn_v.weight | 0x4198dbc0 | 0xc0800 |
| 95 | blk.7.ffn_down.weight | 0x41a4e3c0 | 0x246c000 |
| 96 | blk.7.ffn_gate.weight | 0x43eba3c0 | 0x153f000 |
| 97 | blk.7.ffn_norm.weight | 0x453f93c0 | 0x3800 |
| 98 | blk.7.ffn_up.weight | 0x453fcbc0 | 0x153f000 |
| 99 | blk.8.attn_k.bias | 0x4693bbc0 | 0x800 |
| 100 | blk.8.attn_k.weight | 0x4693c3c0 | 0x93000 |
| 101 | blk.8.attn_norm.weight | 0x469cf3c0 | 0x3800 |
| 102 | blk.8.attn_output.weight | 0x469d2bc0 | 0x543800 |
| 103 | blk.8.attn_q.bias | 0x46f163c0 | 0x3800 |
| 104 | blk.8.attn_q.weight | 0x46f19bc0 | 0x405000 |
| 105 | blk.8.attn_v.bias | 0x4731ebc0 | 0x800 |
| 106 | blk.8.attn_v.weight | 0x4731f3c0 | 0xc0800 |
| 107 | blk.8.ffn_down.weight | 0x473dfbc0 | 0x1bd2800 |
| 108 | blk.8.ffn_gate.weight | 0x48fb23c0 | 0x153f000 |
| 109 | blk.8.ffn_norm.weight | 0x4a4f13c0 | 0x3800 |
| 110 | blk.8.ffn_up.weight | 0x4a4f4bc0 | 0x153f000 |
| 111 | blk.9.attn_k.bias | 0x4ba33bc0 | 0x800 |
| 112 | blk.9.attn_k.weight | 0x4ba343c0 | 0x93000 |
| 113 | blk.9.attn_norm.weight | 0x4bac73c0 | 0x3800 |
| 114 | blk.9.attn_output.weight | 0x4bacabc0 | 0x543800 |
| 115 | blk.9.attn_q.bias | 0x4c00e3c0 | 0x3800 |
| 116 | blk.9.attn_q.weight | 0x4c011bc0 | 0x405000 |
| 117 | blk.9.attn_v.bias | 0x4c416bc0 | 0x800 |
| 118 | blk.9.attn_v.weight | 0x4c4173c0 | 0xc0800 |
| 119 | blk.9.ffn_down.weight | 0x4c4d7bc0 | 0x246c000 |
| 120 | blk.9.ffn_gate.weight | 0x4e943bc0 | 0x1bd2800 |
| 121 | blk.9.ffn_norm.weight | 0x505163c0 | 0x3800 |
| 122 | blk.9.ffn_up.weight | 0x50519bc0 | 0x1bd2800 |
| 123 | blk.10.attn_k.bias | 0x520ec3c0 | 0x800 |
| 124 | blk.10.attn_k.weight | 0x520ecbc0 | 0x93000 |
| 125 | blk.10.attn_norm.weight | 0x5217fbc0 | 0x3800 |
| 126 | blk.10.attn_output.weight | 0x521833c0 | 0x543800 |
| 127 | blk.10.attn_q.bias | 0x526c6bc0 | 0x3800 |
| 128 | blk.10.attn_q.weight | 0x526ca3c0 | 0x405000 |
| 129 | blk.10.attn_v.bias | 0x52acf3c0 | 0x800 |
| 130 | blk.10.attn_v.weight | 0x52acfbc0 | 0xc0800 |
| 131 | blk.10.ffn_down.weight | 0x52b903c0 | 0x246c000 |
| 132 | blk.10.ffn_gate.weight | 0x54ffc3c0 | 0x153f000 |
| 133 | blk.10.ffn_norm.weight | 0x5653b3c0 | 0x3800 |
| 134 | blk.10.ffn_up.weight | 0x5653ebc0 | 0x153f000 |
| 135 | blk.11.attn_k.bias | 0x57a7dbc0 | 0x800 |
| 136 | blk.11.attn_k.weight | 0x57a7e3c0 | 0x93000 |
| 137 | blk.11.attn_norm.weight | 0x57b113c0 | 0x3800 |
| 138 | blk.11.attn_output.weight | 0x57b14bc0 | 0x543800 |
| 139 | blk.11.attn_q.bias | 0x580583c0 | 0x3800 |
| 140 | blk.11.attn_q.weight | 0x5805bbc0 | 0x405000 |
| 141 | blk.11.attn_v.bias | 0x58460bc0 | 0x800 |
| 142 | blk.11.attn_v.weight | 0x584613c0 | 0xc0800 |
| 143 | blk.11.ffn_down.weight | 0x58521bc0 | 0x1bd2800 |
| 144 | blk.11.ffn_gate.weight | 0x5a0f43c0 | 0x153f000 |
| 145 | blk.11.ffn_norm.weight | 0x5b6333c0 | 0x3800 |
| 146 | blk.11.ffn_up.weight | 0x5b636bc0 | 0x153f000 |
| 147 | blk.12.attn_k.bias | 0x5cb75bc0 | 0x800 |
| 148 | blk.12.attn_k.weight | 0x5cb763c0 | 0x93000 |
| 149 | blk.12.attn_norm.weight | 0x5cc093c0 | 0x3800 |
| 150 | blk.12.attn_output.weight | 0x5cc0cbc0 | 0x543800 |
| 151 | blk.12.attn_q.bias | 0x5d1503c0 | 0x3800 |
| 152 | blk.12.attn_q.weight | 0x5d153bc0 | 0x405000 |
| 153 | blk.12.attn_v.bias | 0x5d558bc0 | 0x800 |
| 154 | blk.12.attn_v.weight | 0x5d5593c0 | 0xc0800 |
| 155 | blk.12.ffn_down.weight | 0x5d619bc0 | 0x1bd2800 |
| 156 | blk.12.ffn_gate.weight | 0x5f1ec3c0 | 0x153f000 |
| 157 | blk.12.ffn_norm.weight | 0x6072b3c0 | 0x3800 |
| 158 | blk.12.ffn_up.weight | 0x6072ebc0 | 0x153f000 |
| 159 | blk.13.attn_k.bias | 0x61c6dbc0 | 0x800 |
| 160 | blk.13.attn_k.weight | 0x61c6e3c0 | 0x93000 |
| 161 | blk.13.attn_norm.weight | 0x61d013c0 | 0x3800 |
| 162 | blk.13.attn_output.weight | 0x61d04bc0 | 0x543800 |
| 163 | blk.13.attn_q.bias | 0x622483c0 | 0x3800 |
| 164 | blk.13.attn_q.weight | 0x6224bbc0 | 0x405000 |
| 165 | blk.13.attn_v.bias | 0x62650bc0 | 0x800 |
| 166 | blk.13.attn_v.weight | 0x626513c0 | 0xc0800 |
| 167 | blk.13.ffn_down.weight | 0x62711bc0 | 0x1bd2800 |
| 168 | blk.13.ffn_gate.weight | 0x642e43c0 | 0x153f000 |
| 169 | blk.13.ffn_norm.weight | 0x658233c0 | 0x3800 |
| 170 | blk.13.ffn_up.weight | 0x65826bc0 | 0x153f000 |
| 171 | blk.14.attn_k.bias | 0x66d65bc0 | 0x800 |
| 172 | blk.14.attn_k.weight | 0x66d663c0 | 0xc0800 |
| 173 | blk.14.attn_norm.weight | 0x66e26bc0 | 0x3800 |
| 174 | blk.14.attn_output.weight | 0x66e2a3c0 | 0x543800 |
| 175 | blk.14.attn_q.bias | 0x6736dbc0 | 0x3800 |
| 176 | blk.14.attn_q.weight | 0x673713c0 | 0x543800 |
| 177 | blk.14.attn_v.bias | 0x678b4bc0 | 0x800 |
| 178 | blk.14.attn_v.weight | 0x678b53c0 | 0xc0800 |
| 179 | blk.14.ffn_down.weight | 0x67975bc0 | 0x1bd2800 |
| 180 | blk.14.ffn_gate.weight | 0x695483c0 | 0x153f000 |
| 181 | blk.14.ffn_norm.weight | 0x6aa873c0 | 0x3800 |
| 182 | blk.14.ffn_up.weight | 0x6aa8abc0 | 0x153f000 |
| 183 | blk.15.attn_k.bias | 0x6bfc9bc0 | 0x800 |
| 184 | blk.15.attn_k.weight | 0x6bfca3c0 | 0xc0800 |
| 185 | blk.15.attn_norm.weight | 0x6c08abc0 | 0x3800 |
| 186 | blk.15.attn_output.weight | 0x6c08e3c0 | 0x543800 |
| 187 | blk.15.attn_q.bias | 0x6c5d1bc0 | 0x3800 |
| 188 | blk.15.attn_q.weight | 0x6c5d53c0 | 0x543800 |
| 189 | blk.15.attn_v.bias | 0x6cb18bc0 | 0x800 |
| 190 | blk.15.attn_v.weight | 0x6cb193c0 | 0xc0800 |
| 191 | blk.15.ffn_down.weight | 0x6cbd9bc0 | 0x1bd2800 |
| 192 | blk.15.ffn_gate.weight | 0x6e7ac3c0 | 0x153f000 |
| 193 | blk.15.ffn_norm.weight | 0x6fceb3c0 | 0x3800 |
| 194 | blk.15.ffn_up.weight | 0x6fceebc0 | 0x153f000 |
| 195 | blk.16.attn_k.bias | 0x7122dbc0 | 0x800 |
| 196 | blk.16.attn_k.weight | 0x7122e3c0 | 0xc0800 |
| 197 | blk.16.attn_norm.weight | 0x712eebc0 | 0x3800 |
| 198 | blk.16.attn_output.weight | 0x712f23c0 | 0x543800 |
| 199 | blk.16.attn_q.bias | 0x71835bc0 | 0x3800 |
| 200 | blk.16.attn_q.weight | 0x718393c0 | 0x543800 |
| 201 | blk.16.attn_v.bias | 0x71d7cbc0 | 0x800 |
| 202 | blk.16.attn_v.weight | 0x71d7d3c0 | 0xc0800 |
| 203 | blk.16.ffn_down.weight | 0x71e3dbc0 | 0x1bd2800 |
| 204 | blk.16.ffn_gate.weight | 0x73a103c0 | 0x153f000 |
| 205 | blk.16.ffn_norm.weight | 0x74f4f3c0 | 0x3800 |
| 206 | blk.16.ffn_up.weight | 0x74f52bc0 | 0x153f000 |
| 207 | blk.17.attn_k.bias | 0x76491bc0 | 0x800 |
| 208 | blk.17.attn_k.weight | 0x764923c0 | 0xc0800 |
| 209 | blk.17.attn_norm.weight | 0x76552bc0 | 0x3800 |
| 210 | blk.17.attn_output.weight | 0x765563c0 | 0x543800 |
| 211 | blk.17.attn_q.bias | 0x76a99bc0 | 0x3800 |
| 212 | blk.17.attn_q.weight | 0x76a9d3c0 | 0x543800 |
| 213 | blk.17.attn_v.bias | 0x76fe0bc0 | 0x800 |
| 214 | blk.17.attn_v.weight | 0x76fe13c0 | 0xc0800 |
| 215 | blk.17.ffn_down.weight | 0x770a1bc0 | 0x1bd2800 |
| 216 | blk.17.ffn_gate.weight | 0x78c743c0 | 0x153f000 |
| 217 | blk.17.ffn_norm.weight | 0x7a1b33c0 | 0x3800 |
| 218 | blk.17.ffn_up.weight | 0x7a1b6bc0 | 0x153f000 |
| 219 | blk.18.attn_k.bias | 0x7b6f5bc0 | 0x800 |
| 220 | blk.18.attn_k.weight | 0x7b6f63c0 | 0xc0800 |
| 221 | blk.18.attn_norm.weight | 0x7b7b6bc0 | 0x3800 |
| 222 | blk.18.attn_output.weight | 0x7b7ba3c0 | 0x543800 |
| 223 | blk.18.attn_q.bias | 0x7bcfdbc0 | 0x3800 |
| 224 | blk.18.attn_q.weight | 0x7bd013c0 | 0x543800 |
| 225 | blk.18.attn_v.bias | 0x7c244bc0 | 0x800 |
| 226 | blk.18.attn_v.weight | 0x7c2453c0 | 0xc0800 |
| 227 | blk.18.ffn_down.weight | 0x7c305bc0 | 0x246c000 |
| 228 | blk.18.ffn_gate.weight | 0x7e771bc0 | 0x153f000 |
| 229 | blk.18.ffn_norm.weight | 0x7fcb0bc0 | 0x3800 |
| 230 | blk.18.ffn_up.weight | 0x7fcb43c0 | 0x153f000 |
| 231 | blk.19.attn_k.bias | 0x811f33c0 | 0x800 |
| 232 | blk.19.attn_k.weight | 0x811f3bc0 | 0xc0800 |
| 233 | blk.19.attn_norm.weight | 0x812b43c0 | 0x3800 |
| 234 | blk.19.attn_output.weight | 0x812b7bc0 | 0x543800 |
| 235 | blk.19.attn_q.bias | 0x817fb3c0 | 0x3800 |
| 236 | blk.19.attn_q.weight | 0x817febc0 | 0x543800 |
| 237 | blk.19.attn_v.bias | 0x81d423c0 | 0x800 |
| 238 | blk.19.attn_v.weight | 0x81d42bc0 | 0xc0800 |
| 239 | blk.19.ffn_down.weight | 0x81e033c0 | 0x246c000 |
| 240 | blk.19.ffn_gate.weight | 0x8426f3c0 | 0x153f000 |
| 241 | blk.19.ffn_norm.weight | 0x857ae3c0 | 0x3800 |
| 242 | blk.19.ffn_up.weight | 0x857b1bc0 | 0x153f000 |
| 243 | blk.20.attn_k.bias | 0x86cf0bc0 | 0x800 |
| 244 | blk.20.attn_k.weight | 0x86cf13c0 | 0xc0800 |
| 245 | blk.20.attn_norm.weight | 0x86db1bc0 | 0x3800 |
| 246 | blk.20.attn_output.weight | 0x86db53c0 | 0x543800 |
| 247 | blk.20.attn_q.bias | 0x872f8bc0 | 0x3800 |
| 248 | blk.20.attn_q.weight | 0x872fc3c0 | 0x543800 |
| 249 | blk.20.attn_v.bias | 0x8783fbc0 | 0x800 |
| 250 | blk.20.attn_v.weight | 0x878403c0 | 0xc0800 |
| 251 | blk.20.ffn_down.weight | 0x87900bc0 | 0x246c000 |
| 252 | blk.20.ffn_gate.weight | 0x89d6cbc0 | 0x1bd2800 |
| 253 | blk.20.ffn_norm.weight | 0x8b93f3c0 | 0x3800 |
| 254 | blk.20.ffn_up.weight | 0x8b942bc0 | 0x1bd2800 |
| 255 | blk.21.attn_k.bias | 0x8d5153c0 | 0x800 |
| 256 | blk.21.attn_k.weight | 0x8d515bc0 | 0xc0800 |
| 257 | blk.21.attn_norm.weight | 0x8d5d63c0 | 0x3800 |
| 258 | blk.21.attn_output.weight | 0x8d5d9bc0 | 0x543800 |
| 259 | blk.21.attn_q.bias | 0x8db1d3c0 | 0x3800 |
| 260 | blk.21.attn_q.weight | 0x8db20bc0 | 0x543800 |
| 261 | blk.21.attn_v.bias | 0x8e0643c0 | 0x800 |
| 262 | blk.21.attn_v.weight | 0x8e064bc0 | 0xc0800 |
| 263 | blk.21.ffn_down.weight | 0x8e1253c0 | 0x246c000 |
| 264 | blk.21.ffn_gate.weight | 0x905913c0 | 0x1bd2800 |
| 265 | blk.21.ffn_norm.weight | 0x92163bc0 | 0x3800 |
| 266 | blk.21.ffn_up.weight | 0x921673c0 | 0x1bd2800 |
| 267 | blk.22.attn_k.bias | 0x93d39bc0 | 0x800 |
| 268 | blk.22.attn_k.weight | 0x93d3a3c0 | 0xc0800 |
| 269 | blk.22.attn_norm.weight | 0x93dfabc0 | 0x3800 |
| 270 | blk.22.attn_output.weight | 0x93dfe3c0 | 0x543800 |
| 271 | blk.22.attn_q.bias | 0x94341bc0 | 0x3800 |
| 272 | blk.22.attn_q.weight | 0x943453c0 | 0x543800 |
| 273 | blk.22.attn_v.bias | 0x94888bc0 | 0x800 |
| 274 | blk.22.attn_v.weight | 0x948893c0 | 0xc0800 |
| 275 | blk.22.ffn_down.weight | 0x94949bc0 | 0x246c000 |
| 276 | blk.22.ffn_gate.weight | 0x96db5bc0 | 0x1bd2800 |
| 277 | blk.22.ffn_norm.weight | 0x989883c0 | 0x3800 |
| 278 | blk.22.ffn_up.weight | 0x9898bbc0 | 0x1bd2800 |
| 279 | blk.23.attn_k.bias | 0x9a55e3c0 | 0x800 |
| 280 | blk.23.attn_k.weight | 0x9a55ebc0 | 0xc0800 |
| 281 | blk.23.attn_norm.weight | 0x9a61f3c0 | 0x3800 |
| 282 | blk.23.attn_output.weight | 0x9a622bc0 | 0x543800 |
| 283 | blk.23.attn_q.bias | 0x9ab663c0 | 0x3800 |
| 284 | blk.23.attn_q.weight | 0x9ab69bc0 | 0x543800 |
| 285 | blk.23.attn_v.bias | 0x9b0ad3c0 | 0x800 |
| 286 | blk.23.attn_v.weight | 0x9b0adbc0 | 0xc0800 |
| 287 | blk.23.ffn_down.weight | 0x9b16e3c0 | 0x246c000 |
| 288 | blk.23.ffn_gate.weight | 0x9d5da3c0 | 0x1bd2800 |
| 289 | blk.23.ffn_norm.weight | 0x9f1acbc0 | 0x3800 |
| 290 | blk.23.ffn_up.weight | 0x9f1b03c0 | 0x1bd2800 |
| 291 | blk.24.attn_k.bias | 0xa0d82bc0 | 0x800 |
| 292 | blk.24.attn_k.weight | 0xa0d833c0 | 0xc0800 |
| 293 | blk.24.attn_norm.weight | 0xa0e43bc0 | 0x3800 |
| 294 | blk.24.attn_output.weight | 0xa0e473c0 | 0x543800 |
| 295 | blk.24.attn_q.bias | 0xa138abc0 | 0x3800 |
| 296 | blk.24.attn_q.weight | 0xa138e3c0 | 0x543800 |
| 297 | blk.24.attn_v.bias | 0xa18d1bc0 | 0x800 |
| 298 | blk.24.attn_v.weight | 0xa18d23c0 | 0xc0800 |
| 299 | blk.24.ffn_down.weight | 0xa1992bc0 | 0x246c000 |
| 300 | blk.24.ffn_gate.weight | 0xa3dfebc0 | 0x1bd2800 |
| 301 | blk.24.ffn_norm.weight | 0xa59d13c0 | 0x3800 |
| 302 | blk.24.ffn_up.weight | 0xa59d4bc0 | 0x1bd2800 |
| 303 | blk.25.attn_k.bias | 0xa75a73c0 | 0x800 |
| 304 | blk.25.attn_k.weight | 0xa75a7bc0 | 0xc0800 |
| 305 | blk.25.attn_norm.weight | 0xa76683c0 | 0x3800 |
| 306 | blk.25.attn_output.weight | 0xa766bbc0 | 0x543800 |
| 307 | blk.25.attn_q.bias | 0xa7baf3c0 | 0x3800 |
| 308 | blk.25.attn_q.weight | 0xa7bb2bc0 | 0x543800 |
| 309 | blk.25.attn_v.bias | 0xa80f63c0 | 0x800 |
| 310 | blk.25.attn_v.weight | 0xa80f6bc0 | 0xc0800 |
| 311 | blk.25.ffn_down.weight | 0xa81b73c0 | 0x246c000 |
| 312 | blk.25.ffn_gate.weight | 0xaa6233c0 | 0x1bd2800 |
| 313 | blk.25.ffn_norm.weight | 0xac1f5bc0 | 0x3800 |
| 314 | blk.25.ffn_up.weight | 0xac1f93c0 | 0x1bd2800 |
| 315 | blk.26.attn_k.bias | 0xaddcbbc0 | 0x800 |
| 316 | blk.26.attn_k.weight | 0xaddcc3c0 | 0xc0800 |
| 317 | blk.26.attn_norm.weight | 0xade8cbc0 | 0x3800 |
| 318 | blk.26.attn_output.weight | 0xade903c0 | 0x543800 |
| 319 | blk.26.attn_q.bias | 0xae3d3bc0 | 0x3800 |
| 320 | blk.26.attn_q.weight | 0xae3d73c0 | 0x543800 |
| 321 | blk.26.attn_v.bias | 0xae91abc0 | 0x800 |
| 322 | blk.26.attn_v.weight | 0xae91b3c0 | 0xc0800 |
| 323 | blk.26.ffn_down.weight | 0xae9dbbc0 | 0x246c000 |
| 324 | blk.26.ffn_gate.weight | 0xb0e47bc0 | 0x1bd2800 |
| 325 | blk.26.ffn_norm.weight | 0xb2a1a3c0 | 0x3800 |
| 326 | blk.26.ffn_up.weight | 0xb2a1dbc0 | 0x1bd2800 |
| 327 | blk.27.attn_k.bias | 0xb45f03c0 | 0x800 |
| 328 | blk.27.attn_k.weight | 0xb45f0bc0 | 0xc0800 |
| 329 | blk.27.attn_norm.weight | 0xb46b13c0 | 0x3800 |
| 330 | blk.27.attn_output.weight | 0xb46b4bc0 | 0x543800 |
| 331 | blk.27.attn_q.bias | 0xb4bf83c0 | 0x3800 |
| 332 | blk.27.attn_q.weight | 0xb4bfbbc0 | 0x543800 |
| 333 | blk.27.attn_v.bias | 0xb513f3c0 | 0x800 |
| 334 | blk.27.attn_v.weight | 0xb513fbc0 | 0xc0800 |
| 335 | blk.27.ffn_down.weight | 0xb52003c0 | 0x246c000 |
| 336 | blk.27.ffn_gate.weight | 0xb766c3c0 | 0x1bd2800 |
| 337 | blk.27.ffn_norm.weight | 0xb923ebc0 | 0x3800 |
| 338 | blk.27.ffn_up.weight | 0xb92423c0 | 0x1bd2800 |
Base Tensor Group : ~1B Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 0 | output.weight | Output (W) | (~544M) 543567360 | 3584 x 151665 x 1 x 1 | Q3_K |
| 1 | output_norm.weight | Output Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 2 | token_embd.weight | Token Embedding (W) | (~544M) 543567360 | 3584 x 151665 x 1 x 1 | Q2_K |
- Total elements in base: ( ~1B) 1087138304
- Percentage of total elements: 14.28%
Block 0 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 3 | blk.0.attn_k.bias | Block 0 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 4 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 5 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 6 | blk.0.attn_output.weight | Block 0 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 7 | blk.0.attn_q.bias | Block 0 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 8 | blk.0.attn_q.weight | Block 0 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 9 | blk.0.attn_v.bias | Block 0 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 10 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 11 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 12 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 13 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 14 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.0: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 1 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 15 | blk.1.attn_k.bias | Block 1 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 16 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 17 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 18 | blk.1.attn_output.weight | Block 1 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 19 | blk.1.attn_q.bias | Block 1 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 20 | blk.1.attn_q.weight | Block 1 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 21 | blk.1.attn_v.bias | Block 1 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 22 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 23 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 24 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 25 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 26 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.1: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 2 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 27 | blk.2.attn_k.bias | Block 2 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 28 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 29 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 30 | blk.2.attn_output.weight | Block 2 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 31 | blk.2.attn_q.bias | Block 2 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 32 | blk.2.attn_q.weight | Block 2 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 33 | blk.2.attn_v.bias | Block 2 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 34 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 35 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 36 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 37 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 38 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.2: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 3 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 39 | blk.3.attn_k.bias | Block 3 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 40 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 41 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 42 | blk.3.attn_output.weight | Block 3 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 43 | blk.3.attn_q.bias | Block 3 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 44 | blk.3.attn_q.weight | Block 3 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 45 | blk.3.attn_v.bias | Block 3 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 46 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 47 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 48 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 49 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 50 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.3: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 4 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 51 | blk.4.attn_k.bias | Block 4 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 52 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 53 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 54 | blk.4.attn_output.weight | Block 4 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 55 | blk.4.attn_q.bias | Block 4 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 56 | blk.4.attn_q.weight | Block 4 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 57 | blk.4.attn_v.bias | Block 4 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 58 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 59 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 60 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 61 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 62 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.4: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 5 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 63 | blk.5.attn_k.bias | Block 5 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 64 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 65 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 66 | blk.5.attn_output.weight | Block 5 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 67 | blk.5.attn_q.bias | Block 5 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 68 | blk.5.attn_q.weight | Block 5 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 69 | blk.5.attn_v.bias | Block 5 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 70 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 71 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 72 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 73 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 74 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.5: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 6 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 75 | blk.6.attn_k.bias | Block 6 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 76 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 77 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 78 | blk.6.attn_output.weight | Block 6 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 79 | blk.6.attn_q.bias | Block 6 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 80 | blk.6.attn_q.weight | Block 6 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 81 | blk.6.attn_v.bias | Block 6 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 82 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 83 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 84 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 85 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 86 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.6: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 7 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 87 | blk.7.attn_k.bias | Block 7 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 88 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 89 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 90 | blk.7.attn_output.weight | Block 7 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 91 | blk.7.attn_q.bias | Block 7 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 92 | blk.7.attn_q.weight | Block 7 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 93 | blk.7.attn_v.bias | Block 7 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 94 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 95 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 96 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 97 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 98 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.7: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 8 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 99 | blk.8.attn_k.bias | Block 8 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 100 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 101 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 102 | blk.8.attn_output.weight | Block 8 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 103 | blk.8.attn_q.bias | Block 8 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 104 | blk.8.attn_q.weight | Block 8 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 105 | blk.8.attn_v.bias | Block 8 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 106 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 107 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 108 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 109 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 110 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.8: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 9 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 111 | blk.9.attn_k.bias | Block 9 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 112 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 113 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 114 | blk.9.attn_output.weight | Block 9 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 115 | blk.9.attn_q.bias | Block 9 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 116 | blk.9.attn_q.weight | Block 9 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 117 | blk.9.attn_v.bias | Block 9 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 118 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 119 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 120 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 121 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 122 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.9: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 10 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 123 | blk.10.attn_k.bias | Block 10 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 124 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 125 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 126 | blk.10.attn_output.weight | Block 10 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 127 | blk.10.attn_q.bias | Block 10 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 128 | blk.10.attn_q.weight | Block 10 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 129 | blk.10.attn_v.bias | Block 10 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 130 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 131 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 132 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 133 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 134 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.10: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 11 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 135 | blk.11.attn_k.bias | Block 11 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 136 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 137 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 138 | blk.11.attn_output.weight | Block 11 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 139 | blk.11.attn_q.bias | Block 11 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 140 | blk.11.attn_q.weight | Block 11 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 141 | blk.11.attn_v.bias | Block 11 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 142 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 143 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 144 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 145 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 146 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.11: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 12 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 147 | blk.12.attn_k.bias | Block 12 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 148 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 149 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 150 | blk.12.attn_output.weight | Block 12 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 151 | blk.12.attn_q.bias | Block 12 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 152 | blk.12.attn_q.weight | Block 12 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 153 | blk.12.attn_v.bias | Block 12 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 154 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 155 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 156 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 157 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 158 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.12: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 13 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 159 | blk.13.attn_k.bias | Block 13 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 160 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q2_K |
| 161 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 162 | blk.13.attn_output.weight | Block 13 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 163 | blk.13.attn_q.bias | Block 13 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 164 | blk.13.attn_q.weight | Block 13 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q2_K |
| 165 | blk.13.attn_v.bias | Block 13 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 166 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 167 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 168 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 169 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 170 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.13: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 14 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 171 | blk.14.attn_k.bias | Block 14 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 172 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 173 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 174 | blk.14.attn_output.weight | Block 14 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 175 | blk.14.attn_q.bias | Block 14 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 176 | blk.14.attn_q.weight | Block 14 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 177 | blk.14.attn_v.bias | Block 14 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 178 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 179 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 180 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 181 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 182 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.14: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 15 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 183 | blk.15.attn_k.bias | Block 15 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 184 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 185 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 186 | blk.15.attn_output.weight | Block 15 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 187 | blk.15.attn_q.bias | Block 15 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 188 | blk.15.attn_q.weight | Block 15 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 189 | blk.15.attn_v.bias | Block 15 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 190 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 191 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 192 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 193 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 194 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.15: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 16 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 195 | blk.16.attn_k.bias | Block 16 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 196 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 197 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 198 | blk.16.attn_output.weight | Block 16 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 199 | blk.16.attn_q.bias | Block 16 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 200 | blk.16.attn_q.weight | Block 16 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 201 | blk.16.attn_v.bias | Block 16 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 202 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 203 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 204 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 205 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 206 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.16: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 17 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 207 | blk.17.attn_k.bias | Block 17 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 208 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 209 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 210 | blk.17.attn_output.weight | Block 17 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 211 | blk.17.attn_q.bias | Block 17 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 212 | blk.17.attn_q.weight | Block 17 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 213 | blk.17.attn_v.bias | Block 17 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 214 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 215 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q3_K |
| 216 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 217 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 218 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.17: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 18 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 219 | blk.18.attn_k.bias | Block 18 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 220 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 221 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 222 | blk.18.attn_output.weight | Block 18 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 223 | blk.18.attn_q.bias | Block 18 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 224 | blk.18.attn_q.weight | Block 18 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 225 | blk.18.attn_v.bias | Block 18 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 226 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 227 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 228 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 229 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 230 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.18: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 19 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 231 | blk.19.attn_k.bias | Block 19 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 232 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 233 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 234 | blk.19.attn_output.weight | Block 19 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 235 | blk.19.attn_q.bias | Block 19 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 236 | blk.19.attn_q.weight | Block 19 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 237 | blk.19.attn_v.bias | Block 19 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 238 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 239 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 240 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
| 241 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 242 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q2_K |
- Total elements in blk.19: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 20 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 243 | blk.20.attn_k.bias | Block 20 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 244 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 245 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 246 | blk.20.attn_output.weight | Block 20 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 247 | blk.20.attn_q.bias | Block 20 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 248 | blk.20.attn_q.weight | Block 20 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 249 | blk.20.attn_v.bias | Block 20 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 250 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 251 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 252 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 253 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 254 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.20: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 21 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 255 | blk.21.attn_k.bias | Block 21 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 256 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 257 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 258 | blk.21.attn_output.weight | Block 21 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 259 | blk.21.attn_q.bias | Block 21 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 260 | blk.21.attn_q.weight | Block 21 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 261 | blk.21.attn_v.bias | Block 21 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 262 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 263 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 264 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 265 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 266 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.21: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 22 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 267 | blk.22.attn_k.bias | Block 22 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 268 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 269 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 270 | blk.22.attn_output.weight | Block 22 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 271 | blk.22.attn_q.bias | Block 22 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 272 | blk.22.attn_q.weight | Block 22 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 273 | blk.22.attn_v.bias | Block 22 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 274 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 275 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 276 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 277 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 278 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.22: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 23 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 279 | blk.23.attn_k.bias | Block 23 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 280 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 281 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 282 | blk.23.attn_output.weight | Block 23 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 283 | blk.23.attn_q.bias | Block 23 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 284 | blk.23.attn_q.weight | Block 23 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 285 | blk.23.attn_v.bias | Block 23 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 286 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 287 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 288 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 289 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 290 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.23: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 24 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 291 | blk.24.attn_k.bias | Block 24 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 292 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 293 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 294 | blk.24.attn_output.weight | Block 24 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 295 | blk.24.attn_q.bias | Block 24 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 296 | blk.24.attn_q.weight | Block 24 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 297 | blk.24.attn_v.bias | Block 24 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 298 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 299 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 300 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 301 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 302 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.24: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 25 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 303 | blk.25.attn_k.bias | Block 25 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 304 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 305 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 306 | blk.25.attn_output.weight | Block 25 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 307 | blk.25.attn_q.bias | Block 25 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 308 | blk.25.attn_q.weight | Block 25 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 309 | blk.25.attn_v.bias | Block 25 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 310 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 311 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 312 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 313 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 314 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.25: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 26 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 315 | blk.26.attn_k.bias | Block 26 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 316 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 317 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 318 | blk.26.attn_output.weight | Block 26 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 319 | blk.26.attn_q.bias | Block 26 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 320 | blk.26.attn_q.weight | Block 26 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 321 | blk.26.attn_v.bias | Block 26 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 322 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 323 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 324 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 325 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 326 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.26: (~233M) 233057792
- Percentage of total elements: 3.06%
Block 27 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 327 | blk.27.attn_k.bias | Block 27 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 328 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 329 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 330 | blk.27.attn_output.weight | Block 27 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 331 | blk.27.attn_q.bias | Block 27 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 332 | blk.27.attn_q.weight | Block 27 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q3_K |
| 333 | blk.27.attn_v.bias | Block 27 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 334 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q3_K |
| 335 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q4_K |
| 336 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
| 337 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 338 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q3_K |
- Total elements in blk.27: (~233M) 233057792
- Percentage of total elements: 3.06%