Mistral-Small-3.2-24B-Instruct-2506-pruned-GGUF
/
scores
/Mistral-Small-3.2-24B-Instruct-2506-pruned-Q4_K_M.md
Mistral-Small-3.2-24B-Instruct-pruned-Q4_K_M.gguf - GGUF Internal File Dump
- Endian: LITTLE endian
Key Value Metadata Store
There are 49 key-value pairs in this file
| POS | TYPE | Count | Key | Value |
|---|---|---|---|---|
| 1 | UINT32 | 1 | GGUF.version | 3 |
| 2 | UINT64 | 1 | GGUF.tensor_count | 345 |
| 3 | UINT64 | 1 | GGUF.kv_count | 46 |
| 4 | STRING | 1 | general.architecture | llama |
| 5 | STRING | 1 | general.type | model |
| 6 | STRING | 1 | general.name | Mistral Small 3.2 24B Instruct 2506 |
| 7 | STRING | 1 | general.version | 2506 |
| 8 | STRING | 1 | general.finetune | Instruct |
| 9 | STRING | 1 | general.basename | Mistral-Small-3.2 |
| 10 | STRING | 1 | general.size_label | 24B |
| 11 | STRING | 1 | general.license | apache-2.0 |
| 12 | UINT32 | 1 | general.base_model.count | 1 |
| 13 | STRING | 1 | general.base_model.0.name | Mistral Small 3.1 24B Base 2503 |
| 14 | STRING | 1 | general.base_model.0.version | 2503 |
| 15 | STRING | 1 | general.base_model.0.organization | Mistralai |
| 16 | STRING | 1 | general.base_model.0.repo_url | https://huggingface.co/mistral...istral-Small-3.1-24B-Base-2503 |
| 17 | [STRING] | 1 | general.tags | [ image-text-to-text ] |
| 18 | [STRING] | 24 | general.languages | [ en, fr, de, es, pt, ... ] |
| 19 | UINT32 | 1 | llama.context_length | 131072 |
| 20 | UINT32 | 1 | llama.embedding_length | 5120 |
| 21 | UINT32 | 1 | llama.feed_forward_length | 32768 |
| 22 | UINT32 | 1 | llama.attention.head_count | 32 |
| 23 | UINT32 | 1 | llama.attention.head_count_kv | 8 |
| 24 | FLOAT32 | 1 | llama.rope.freq_base | 1000000000.0 |
| 25 | FLOAT32 | 1 | llama.attention.layer_norm_rms_epsilon | 1e-05 |
| 26 | UINT32 | 1 | llama.attention.key_length | 128 |
| 27 | UINT32 | 1 | llama.attention.value_length | 128 |
| 28 | UINT32 | 1 | llama.vocab_size | 131072 |
| 29 | UINT32 | 1 | llama.rope.dimension_count | 128 |
| 30 | STRING | 1 | tokenizer.ggml.model | gpt2 |
| 31 | STRING | 1 | tokenizer.ggml.pre | tekken |
| 32 | [STRING] | 131072 | tokenizer.ggml.tokens | [ <unk>, <s>, </s>, [INST], [/INST], ... ] |
| 33 | [INT32] | 131072 | tokenizer.ggml.token_type | [ 3, 3, 3, 3, 3, 3, 3, ... ] |
| 34 | [STRING] | 269443 | tokenizer.ggml.merges | [ Ġ Ġ, Ġ t, e r, i n, Ġ ĠĠĠ, ... ] |
| 35 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 1 |
| 36 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 2 |
| 37 | UINT32 | 1 | tokenizer.ggml.unknown_token_id | 0 |
| 38 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 11 |
| 39 | BOOL | 1 | tokenizer.ggml.add_bos_token | True |
| 40 | BOOL | 1 | tokenizer.ggml.add_sep_token | False |
| 41 | BOOL | 1 | tokenizer.ggml.add_eos_token | False |
| 42 | BOOL | 1 | tokenizer.ggml.add_space_prefix | False |
| 43 | UINT32 | 1 | llama.block_count | 38 |
| 44 | UINT32 | 1 | general.quantization_version | 2 |
| 45 | UINT32 | 1 | general.file_type | 15 |
| 46 | STRING | 1 | quantize.imatrix.file | ./imatrix/imatrix-Mistral-Smal...24B-Instruct-pruned-medium.dat |
| 47 | STRING | 1 | quantize.imatrix.dataset | ../../datasets/imatrix/text_eur_medium.txt |
| 48 | UINT32 | 1 | quantize.imatrix.entries_count | 266 |
| 49 | UINT32 | 1 | quantize.imatrix.chunks_count | 1778 |
Tensors Overview ~22B Elements
Total number of elements in all tensors: 22460892160 Elements
- Mistral-Small-3.2-24B-Instruct-pruned-Q4_K_M.gguf - GGUF Internal File Dump
- Key Value Metadata Store
- Tensors Overview ~22B Elements
- Tensor Data Offset
- Base Tensor Group : ~1B Elements
- Block 0 Tensor Group : ~556M Elements
- Block 1 Tensor Group : ~556M Elements
- Block 2 Tensor Group : ~556M Elements
- Block 3 Tensor Group : ~556M Elements
- Block 4 Tensor Group : ~556M Elements
- Block 5 Tensor Group : ~556M Elements
- Block 6 Tensor Group : ~556M Elements
- Block 7 Tensor Group : ~556M Elements
- Block 8 Tensor Group : ~556M Elements
- Block 9 Tensor Group : ~556M Elements
- Block 10 Tensor Group : ~556M Elements
- Block 11 Tensor Group : ~556M Elements
- Block 12 Tensor Group : ~556M Elements
- Block 13 Tensor Group : ~556M Elements
- Block 14 Tensor Group : ~556M Elements
- Block 15 Tensor Group : ~556M Elements
- Block 16 Tensor Group : ~556M Elements
- Block 17 Tensor Group : ~556M Elements
- Block 18 Tensor Group : ~556M Elements
- Block 19 Tensor Group : ~556M Elements
- Block 20 Tensor Group : ~556M Elements
- Block 21 Tensor Group : ~556M Elements
- Block 22 Tensor Group : ~556M Elements
- Block 23 Tensor Group : ~556M Elements
- Block 24 Tensor Group : ~556M Elements
- Block 25 Tensor Group : ~556M Elements
- Block 26 Tensor Group : ~556M Elements
- Block 27 Tensor Group : ~556M Elements
- Block 28 Tensor Group : ~556M Elements
- Block 29 Tensor Group : ~556M Elements
- Block 30 Tensor Group : ~556M Elements
- Block 31 Tensor Group : ~556M Elements
- Block 32 Tensor Group : ~556M Elements
- Block 33 Tensor Group : ~556M Elements
- Block 34 Tensor Group : ~556M Elements
- Block 35 Tensor Group : ~556M Elements
- Block 36 Tensor Group : ~556M Elements
- Block 37 Tensor Group : ~556M 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 | 0x7841e0 | 0x16800000 |
| 1 | output_norm.weight | 0x16f841e0 | 0x5000 |
| 2 | token_embd.weight | 0x16f891e0 | 0x11300000 |
| 3 | blk.0.attn_k.weight | 0x282891e0 | 0x2d0000 |
| 4 | blk.0.attn_norm.weight | 0x285591e0 | 0x5000 |
| 5 | blk.0.attn_output.weight | 0x2855e1e0 | 0xb40000 |
| 6 | blk.0.attn_q.weight | 0x2909e1e0 | 0xb40000 |
| 7 | blk.0.attn_v.weight | 0x29bde1e0 | 0x370000 |
| 8 | blk.0.ffn_down.weight | 0x29f4e1e0 | 0x6e00000 |
| 9 | blk.0.ffn_gate.weight | 0x30d4e1e0 | 0x5a00000 |
| 10 | blk.0.ffn_norm.weight | 0x3674e1e0 | 0x5000 |
| 11 | blk.0.ffn_up.weight | 0x367531e0 | 0x5a00000 |
| 12 | blk.1.attn_k.weight | 0x3c1531e0 | 0x2d0000 |
| 13 | blk.1.attn_norm.weight | 0x3c4231e0 | 0x5000 |
| 14 | blk.1.attn_output.weight | 0x3c4281e0 | 0xb40000 |
| 15 | blk.1.attn_q.weight | 0x3cf681e0 | 0xb40000 |
| 16 | blk.1.attn_v.weight | 0x3daa81e0 | 0x370000 |
| 17 | blk.1.ffn_down.weight | 0x3de181e0 | 0x6e00000 |
| 18 | blk.1.ffn_gate.weight | 0x44c181e0 | 0x5a00000 |
| 19 | blk.1.ffn_norm.weight | 0x4a6181e0 | 0x5000 |
| 20 | blk.1.ffn_up.weight | 0x4a61d1e0 | 0x5a00000 |
| 21 | blk.2.attn_k.weight | 0x5001d1e0 | 0x2d0000 |
| 22 | blk.2.attn_norm.weight | 0x502ed1e0 | 0x5000 |
| 23 | blk.2.attn_output.weight | 0x502f21e0 | 0xb40000 |
| 24 | blk.2.attn_q.weight | 0x50e321e0 | 0xb40000 |
| 25 | blk.2.attn_v.weight | 0x519721e0 | 0x370000 |
| 26 | blk.2.ffn_down.weight | 0x51ce21e0 | 0x6e00000 |
| 27 | blk.2.ffn_gate.weight | 0x58ae21e0 | 0x5a00000 |
| 28 | blk.2.ffn_norm.weight | 0x5e4e21e0 | 0x5000 |
| 29 | blk.2.ffn_up.weight | 0x5e4e71e0 | 0x5a00000 |
| 30 | blk.3.attn_k.weight | 0x63ee71e0 | 0x2d0000 |
| 31 | blk.3.attn_norm.weight | 0x641b71e0 | 0x5000 |
| 32 | blk.3.attn_output.weight | 0x641bc1e0 | 0xb40000 |
| 33 | blk.3.attn_q.weight | 0x64cfc1e0 | 0xb40000 |
| 34 | blk.3.attn_v.weight | 0x6583c1e0 | 0x370000 |
| 35 | blk.3.ffn_down.weight | 0x65bac1e0 | 0x6e00000 |
| 36 | blk.3.ffn_gate.weight | 0x6c9ac1e0 | 0x5a00000 |
| 37 | blk.3.ffn_norm.weight | 0x723ac1e0 | 0x5000 |
| 38 | blk.3.ffn_up.weight | 0x723b11e0 | 0x5a00000 |
| 39 | blk.4.attn_k.weight | 0x77db11e0 | 0x2d0000 |
| 40 | blk.4.attn_norm.weight | 0x780811e0 | 0x5000 |
| 41 | blk.4.attn_output.weight | 0x780861e0 | 0xb40000 |
| 42 | blk.4.attn_q.weight | 0x78bc61e0 | 0xb40000 |
| 43 | blk.4.attn_v.weight | 0x797061e0 | 0x370000 |
| 44 | blk.4.ffn_down.weight | 0x79a761e0 | 0x6e00000 |
| 45 | blk.4.ffn_gate.weight | 0x808761e0 | 0x5a00000 |
| 46 | blk.4.ffn_norm.weight | 0x862761e0 | 0x5000 |
| 47 | blk.4.ffn_up.weight | 0x8627b1e0 | 0x5a00000 |
| 48 | blk.5.attn_k.weight | 0x8bc7b1e0 | 0x2d0000 |
| 49 | blk.5.attn_norm.weight | 0x8bf4b1e0 | 0x5000 |
| 50 | blk.5.attn_output.weight | 0x8bf501e0 | 0xb40000 |
| 51 | blk.5.attn_q.weight | 0x8ca901e0 | 0xb40000 |
| 52 | blk.5.attn_v.weight | 0x8d5d01e0 | 0x370000 |
| 53 | blk.5.ffn_down.weight | 0x8d9401e0 | 0x6e00000 |
| 54 | blk.5.ffn_gate.weight | 0x947401e0 | 0x5a00000 |
| 55 | blk.5.ffn_norm.weight | 0x9a1401e0 | 0x5000 |
| 56 | blk.5.ffn_up.weight | 0x9a1451e0 | 0x5a00000 |
| 57 | blk.6.attn_k.weight | 0x9fb451e0 | 0x2d0000 |
| 58 | blk.6.attn_norm.weight | 0x9fe151e0 | 0x5000 |
| 59 | blk.6.attn_output.weight | 0x9fe1a1e0 | 0xb40000 |
| 60 | blk.6.attn_q.weight | 0xa095a1e0 | 0xb40000 |
| 61 | blk.6.attn_v.weight | 0xa149a1e0 | 0x370000 |
| 62 | blk.6.ffn_down.weight | 0xa180a1e0 | 0x6e00000 |
| 63 | blk.6.ffn_gate.weight | 0xa860a1e0 | 0x5a00000 |
| 64 | blk.6.ffn_norm.weight | 0xae00a1e0 | 0x5000 |
| 65 | blk.6.ffn_up.weight | 0xae00f1e0 | 0x5a00000 |
| 66 | blk.7.attn_k.weight | 0xb3a0f1e0 | 0x2d0000 |
| 67 | blk.7.attn_norm.weight | 0xb3cdf1e0 | 0x5000 |
| 68 | blk.7.attn_output.weight | 0xb3ce41e0 | 0xb40000 |
| 69 | blk.7.attn_q.weight | 0xb48241e0 | 0xb40000 |
| 70 | blk.7.attn_v.weight | 0xb53641e0 | 0x370000 |
| 71 | blk.7.ffn_down.weight | 0xb56d41e0 | 0x6e00000 |
| 72 | blk.7.ffn_gate.weight | 0xbc4d41e0 | 0x5a00000 |
| 73 | blk.7.ffn_norm.weight | 0xc1ed41e0 | 0x5000 |
| 74 | blk.7.ffn_up.weight | 0xc1ed91e0 | 0x5a00000 |
| 75 | blk.8.attn_k.weight | 0xc78d91e0 | 0x2d0000 |
| 76 | blk.8.attn_norm.weight | 0xc7ba91e0 | 0x5000 |
| 77 | blk.8.attn_output.weight | 0xc7bae1e0 | 0xb40000 |
| 78 | blk.8.attn_q.weight | 0xc86ee1e0 | 0xb40000 |
| 79 | blk.8.attn_v.weight | 0xc922e1e0 | 0x370000 |
| 80 | blk.8.ffn_down.weight | 0xc959e1e0 | 0x6e00000 |
| 81 | blk.8.ffn_gate.weight | 0xd039e1e0 | 0x5a00000 |
| 82 | blk.8.ffn_norm.weight | 0xd5d9e1e0 | 0x5000 |
| 83 | blk.8.ffn_up.weight | 0xd5da31e0 | 0x5a00000 |
| 84 | blk.9.attn_k.weight | 0xdb7a31e0 | 0x2d0000 |
| 85 | blk.9.attn_norm.weight | 0xdba731e0 | 0x5000 |
| 86 | blk.9.attn_output.weight | 0xdba781e0 | 0xb40000 |
| 87 | blk.9.attn_q.weight | 0xdc5b81e0 | 0xb40000 |
| 88 | blk.9.attn_v.weight | 0xdd0f81e0 | 0x370000 |
| 89 | blk.9.ffn_down.weight | 0xdd4681e0 | 0x6e00000 |
| 90 | blk.9.ffn_gate.weight | 0xe42681e0 | 0x5a00000 |
| 91 | blk.9.ffn_norm.weight | 0xe9c681e0 | 0x5000 |
| 92 | blk.9.ffn_up.weight | 0xe9c6d1e0 | 0x5a00000 |
| 93 | blk.10.attn_k.weight | 0xef66d1e0 | 0x2d0000 |
| 94 | blk.10.attn_norm.weight | 0xef93d1e0 | 0x5000 |
| 95 | blk.10.attn_output.weight | 0xef9421e0 | 0xb40000 |
| 96 | blk.10.attn_q.weight | 0xf04821e0 | 0xb40000 |
| 97 | blk.10.attn_v.weight | 0xf0fc21e0 | 0x370000 |
| 98 | blk.10.ffn_down.weight | 0xf13321e0 | 0x6e00000 |
| 99 | blk.10.ffn_gate.weight | 0xf81321e0 | 0x5a00000 |
| 100 | blk.10.ffn_norm.weight | 0xfdb321e0 | 0x5000 |
| 101 | blk.10.ffn_up.weight | 0xfdb371e0 | 0x5a00000 |
| 102 | blk.11.attn_k.weight | 0x1035371e0 | 0x2d0000 |
| 103 | blk.11.attn_norm.weight | 0x1038071e0 | 0x5000 |
| 104 | blk.11.attn_output.weight | 0x10380c1e0 | 0xb40000 |
| 105 | blk.11.attn_q.weight | 0x10434c1e0 | 0xb40000 |
| 106 | blk.11.attn_v.weight | 0x104e8c1e0 | 0x370000 |
| 107 | blk.11.ffn_down.weight | 0x1051fc1e0 | 0x6e00000 |
| 108 | blk.11.ffn_gate.weight | 0x10bffc1e0 | 0x5a00000 |
| 109 | blk.11.ffn_norm.weight | 0x1119fc1e0 | 0x5000 |
| 110 | blk.11.ffn_up.weight | 0x111a011e0 | 0x5a00000 |
| 111 | blk.12.attn_k.weight | 0x1174011e0 | 0x2d0000 |
| 112 | blk.12.attn_norm.weight | 0x1176d11e0 | 0x5000 |
| 113 | blk.12.attn_output.weight | 0x1176d61e0 | 0xb40000 |
| 114 | blk.12.attn_q.weight | 0x1182161e0 | 0xb40000 |
| 115 | blk.12.attn_v.weight | 0x118d561e0 | 0x370000 |
| 116 | blk.12.ffn_down.weight | 0x1190c61e0 | 0x6e00000 |
| 117 | blk.12.ffn_gate.weight | 0x11fec61e0 | 0x5a00000 |
| 118 | blk.12.ffn_norm.weight | 0x1258c61e0 | 0x5000 |
| 119 | blk.12.ffn_up.weight | 0x1258cb1e0 | 0x5a00000 |
| 120 | blk.13.attn_k.weight | 0x12b2cb1e0 | 0x2d0000 |
| 121 | blk.13.attn_norm.weight | 0x12b59b1e0 | 0x5000 |
| 122 | blk.13.attn_output.weight | 0x12b5a01e0 | 0xb40000 |
| 123 | blk.13.attn_q.weight | 0x12c0e01e0 | 0xb40000 |
| 124 | blk.13.attn_v.weight | 0x12cc201e0 | 0x370000 |
| 125 | blk.13.ffn_down.weight | 0x12cf901e0 | 0x6e00000 |
| 126 | blk.13.ffn_gate.weight | 0x133d901e0 | 0x5a00000 |
| 127 | blk.13.ffn_norm.weight | 0x1397901e0 | 0x5000 |
| 128 | blk.13.ffn_up.weight | 0x1397951e0 | 0x5a00000 |
| 129 | blk.14.attn_k.weight | 0x13f1951e0 | 0x2d0000 |
| 130 | blk.14.attn_norm.weight | 0x13f4651e0 | 0x5000 |
| 131 | blk.14.attn_output.weight | 0x13f46a1e0 | 0xb40000 |
| 132 | blk.14.attn_q.weight | 0x13ffaa1e0 | 0xb40000 |
| 133 | blk.14.attn_v.weight | 0x140aea1e0 | 0x370000 |
| 134 | blk.14.ffn_down.weight | 0x140e5a1e0 | 0x6e00000 |
| 135 | blk.14.ffn_gate.weight | 0x147c5a1e0 | 0x5a00000 |
| 136 | blk.14.ffn_norm.weight | 0x14d65a1e0 | 0x5000 |
| 137 | blk.14.ffn_up.weight | 0x14d65f1e0 | 0x5a00000 |
| 138 | blk.15.attn_k.weight | 0x15305f1e0 | 0x2d0000 |
| 139 | blk.15.attn_norm.weight | 0x15332f1e0 | 0x5000 |
| 140 | blk.15.attn_output.weight | 0x1533341e0 | 0xb40000 |
| 141 | blk.15.attn_q.weight | 0x153e741e0 | 0xb40000 |
| 142 | blk.15.attn_v.weight | 0x1549b41e0 | 0x370000 |
| 143 | blk.15.ffn_down.weight | 0x154d241e0 | 0x6e00000 |
| 144 | blk.15.ffn_gate.weight | 0x15bb241e0 | 0x5a00000 |
| 145 | blk.15.ffn_norm.weight | 0x1615241e0 | 0x5000 |
| 146 | blk.15.ffn_up.weight | 0x1615291e0 | 0x5a00000 |
| 147 | blk.16.attn_k.weight | 0x166f291e0 | 0x2d0000 |
| 148 | blk.16.attn_norm.weight | 0x1671f91e0 | 0x5000 |
| 149 | blk.16.attn_output.weight | 0x1671fe1e0 | 0xb40000 |
| 150 | blk.16.attn_q.weight | 0x167d3e1e0 | 0xb40000 |
| 151 | blk.16.attn_v.weight | 0x16887e1e0 | 0x370000 |
| 152 | blk.16.ffn_down.weight | 0x168bee1e0 | 0x6e00000 |
| 153 | blk.16.ffn_gate.weight | 0x16f9ee1e0 | 0x5a00000 |
| 154 | blk.16.ffn_norm.weight | 0x1753ee1e0 | 0x5000 |
| 155 | blk.16.ffn_up.weight | 0x1753f31e0 | 0x5a00000 |
| 156 | blk.17.attn_k.weight | 0x17adf31e0 | 0x226000 |
| 157 | blk.17.attn_norm.weight | 0x17b0191e0 | 0x5000 |
| 158 | blk.17.attn_output.weight | 0x17b01e1e0 | 0xb40000 |
| 159 | blk.17.attn_q.weight | 0x17bb5e1e0 | 0x898000 |
| 160 | blk.17.attn_v.weight | 0x17c3f61e0 | 0x2d0000 |
| 161 | blk.17.ffn_down.weight | 0x17c6c61e0 | 0x6e00000 |
| 162 | blk.17.ffn_gate.weight | 0x1834c61e0 | 0x5a00000 |
| 163 | blk.17.ffn_norm.weight | 0x188ec61e0 | 0x5000 |
| 164 | blk.17.ffn_up.weight | 0x188ecb1e0 | 0x5a00000 |
| 165 | blk.18.attn_k.weight | 0x18e8cb1e0 | 0x226000 |
| 166 | blk.18.attn_norm.weight | 0x18eaf11e0 | 0x5000 |
| 167 | blk.18.attn_output.weight | 0x18eaf61e0 | 0xb40000 |
| 168 | blk.18.attn_q.weight | 0x18f6361e0 | 0x898000 |
| 169 | blk.18.attn_v.weight | 0x18fece1e0 | 0x2d0000 |
| 170 | blk.18.ffn_down.weight | 0x19019e1e0 | 0x6e00000 |
| 171 | blk.18.ffn_gate.weight | 0x196f9e1e0 | 0x5a00000 |
| 172 | blk.18.ffn_norm.weight | 0x19c99e1e0 | 0x5000 |
| 173 | blk.18.ffn_up.weight | 0x19c9a31e0 | 0x5a00000 |
| 174 | blk.19.attn_k.weight | 0x1a23a31e0 | 0x2d0000 |
| 175 | blk.19.attn_norm.weight | 0x1a26731e0 | 0x5000 |
| 176 | blk.19.attn_output.weight | 0x1a26781e0 | 0xb40000 |
| 177 | blk.19.attn_q.weight | 0x1a31b81e0 | 0xb40000 |
| 178 | blk.19.attn_v.weight | 0x1a3cf81e0 | 0x370000 |
| 179 | blk.19.ffn_down.weight | 0x1a40681e0 | 0x6e00000 |
| 180 | blk.19.ffn_gate.weight | 0x1aae681e0 | 0x5a00000 |
| 181 | blk.19.ffn_norm.weight | 0x1b08681e0 | 0x5000 |
| 182 | blk.19.ffn_up.weight | 0x1b086d1e0 | 0x5a00000 |
| 183 | blk.20.attn_k.weight | 0x1b626d1e0 | 0x226000 |
| 184 | blk.20.attn_norm.weight | 0x1b64931e0 | 0x5000 |
| 185 | blk.20.attn_output.weight | 0x1b64981e0 | 0xb40000 |
| 186 | blk.20.attn_q.weight | 0x1b6fd81e0 | 0x898000 |
| 187 | blk.20.attn_v.weight | 0x1b78701e0 | 0x2d0000 |
| 188 | blk.20.ffn_down.weight | 0x1b7b401e0 | 0x6e00000 |
| 189 | blk.20.ffn_gate.weight | 0x1be9401e0 | 0x44c0000 |
| 190 | blk.20.ffn_norm.weight | 0x1c2e001e0 | 0x5000 |
| 191 | blk.20.ffn_up.weight | 0x1c2e051e0 | 0x44c0000 |
| 192 | blk.21.attn_k.weight | 0x1c72c51e0 | 0x2d0000 |
| 193 | blk.21.attn_norm.weight | 0x1c75951e0 | 0x5000 |
| 194 | blk.21.attn_output.weight | 0x1c759a1e0 | 0xb40000 |
| 195 | blk.21.attn_q.weight | 0x1c80da1e0 | 0xb40000 |
| 196 | blk.21.attn_v.weight | 0x1c8c1a1e0 | 0x370000 |
| 197 | blk.21.ffn_down.weight | 0x1c8f8a1e0 | 0x6e00000 |
| 198 | blk.21.ffn_gate.weight | 0x1cfd8a1e0 | 0x44c0000 |
| 199 | blk.21.ffn_norm.weight | 0x1d424a1e0 | 0x5000 |
| 200 | blk.21.ffn_up.weight | 0x1d424f1e0 | 0x44c0000 |
| 201 | blk.22.attn_k.weight | 0x1d870f1e0 | 0x226000 |
| 202 | blk.22.attn_norm.weight | 0x1d89351e0 | 0x5000 |
| 203 | blk.22.attn_output.weight | 0x1d893a1e0 | 0xb40000 |
| 204 | blk.22.attn_q.weight | 0x1d947a1e0 | 0x898000 |
| 205 | blk.22.attn_v.weight | 0x1d9d121e0 | 0x2d0000 |
| 206 | blk.22.ffn_down.weight | 0x1d9fe21e0 | 0x6e00000 |
| 207 | blk.22.ffn_gate.weight | 0x1e0de21e0 | 0x44c0000 |
| 208 | blk.22.ffn_norm.weight | 0x1e52a21e0 | 0x5000 |
| 209 | blk.22.ffn_up.weight | 0x1e52a71e0 | 0x44c0000 |
| 210 | blk.23.attn_k.weight | 0x1e97671e0 | 0x226000 |
| 211 | blk.23.attn_norm.weight | 0x1e998d1e0 | 0x5000 |
| 212 | blk.23.attn_output.weight | 0x1e99921e0 | 0xb40000 |
| 213 | blk.23.attn_q.weight | 0x1ea4d21e0 | 0x898000 |
| 214 | blk.23.attn_v.weight | 0x1ead6a1e0 | 0x2d0000 |
| 215 | blk.23.ffn_down.weight | 0x1eb03a1e0 | 0x6e00000 |
| 216 | blk.23.ffn_gate.weight | 0x1f1e3a1e0 | 0x44c0000 |
| 217 | blk.23.ffn_norm.weight | 0x1f62fa1e0 | 0x5000 |
| 218 | blk.23.ffn_up.weight | 0x1f62ff1e0 | 0x44c0000 |
| 219 | blk.24.attn_k.weight | 0x1fa7bf1e0 | 0x226000 |
| 220 | blk.24.attn_norm.weight | 0x1fa9e51e0 | 0x5000 |
| 221 | blk.24.attn_output.weight | 0x1fa9ea1e0 | 0xb40000 |
| 222 | blk.24.attn_q.weight | 0x1fb52a1e0 | 0x898000 |
| 223 | blk.24.attn_v.weight | 0x1fbdc21e0 | 0x2d0000 |
| 224 | blk.24.ffn_down.weight | 0x1fc0921e0 | 0x6e00000 |
| 225 | blk.24.ffn_gate.weight | 0x202e921e0 | 0x44c0000 |
| 226 | blk.24.ffn_norm.weight | 0x2073521e0 | 0x5000 |
| 227 | blk.24.ffn_up.weight | 0x2073571e0 | 0x44c0000 |
| 228 | blk.25.attn_k.weight | 0x20b8171e0 | 0x226000 |
| 229 | blk.25.attn_norm.weight | 0x20ba3d1e0 | 0x5000 |
| 230 | blk.25.attn_output.weight | 0x20ba421e0 | 0xb40000 |
| 231 | blk.25.attn_q.weight | 0x20c5821e0 | 0x898000 |
| 232 | blk.25.attn_v.weight | 0x20ce1a1e0 | 0x2d0000 |
| 233 | blk.25.ffn_down.weight | 0x20d0ea1e0 | 0x6e00000 |
| 234 | blk.25.ffn_gate.weight | 0x213eea1e0 | 0x44c0000 |
| 235 | blk.25.ffn_norm.weight | 0x2183aa1e0 | 0x5000 |
| 236 | blk.25.ffn_up.weight | 0x2183af1e0 | 0x44c0000 |
| 237 | blk.26.attn_k.weight | 0x21c86f1e0 | 0x226000 |
| 238 | blk.26.attn_norm.weight | 0x21ca951e0 | 0x5000 |
| 239 | blk.26.attn_output.weight | 0x21ca9a1e0 | 0xb40000 |
| 240 | blk.26.attn_q.weight | 0x21d5da1e0 | 0x898000 |
| 241 | blk.26.attn_v.weight | 0x21de721e0 | 0x2d0000 |
| 242 | blk.26.ffn_down.weight | 0x21e1421e0 | 0x6e00000 |
| 243 | blk.26.ffn_gate.weight | 0x224f421e0 | 0x44c0000 |
| 244 | blk.26.ffn_norm.weight | 0x2294021e0 | 0x5000 |
| 245 | blk.26.ffn_up.weight | 0x2294071e0 | 0x44c0000 |
| 246 | blk.27.attn_k.weight | 0x22d8c71e0 | 0x2d0000 |
| 247 | blk.27.attn_norm.weight | 0x22db971e0 | 0x5000 |
| 248 | blk.27.attn_output.weight | 0x22db9c1e0 | 0xb40000 |
| 249 | blk.27.attn_q.weight | 0x22e6dc1e0 | 0xb40000 |
| 250 | blk.27.attn_v.weight | 0x22f21c1e0 | 0x370000 |
| 251 | blk.27.ffn_down.weight | 0x22f58c1e0 | 0x6e00000 |
| 252 | blk.27.ffn_gate.weight | 0x23638c1e0 | 0x44c0000 |
| 253 | blk.27.ffn_norm.weight | 0x23a84c1e0 | 0x5000 |
| 254 | blk.27.ffn_up.weight | 0x23a8511e0 | 0x44c0000 |
| 255 | blk.28.attn_k.weight | 0x23ed111e0 | 0x226000 |
| 256 | blk.28.attn_norm.weight | 0x23ef371e0 | 0x5000 |
| 257 | blk.28.attn_output.weight | 0x23ef3c1e0 | 0xb40000 |
| 258 | blk.28.attn_q.weight | 0x23fa7c1e0 | 0x898000 |
| 259 | blk.28.attn_v.weight | 0x2403141e0 | 0x2d0000 |
| 260 | blk.28.ffn_down.weight | 0x2405e41e0 | 0x6e00000 |
| 261 | blk.28.ffn_gate.weight | 0x2473e41e0 | 0x44c0000 |
| 262 | blk.28.ffn_norm.weight | 0x24b8a41e0 | 0x5000 |
| 263 | blk.28.ffn_up.weight | 0x24b8a91e0 | 0x44c0000 |
| 264 | blk.29.attn_k.weight | 0x24fd691e0 | 0x226000 |
| 265 | blk.29.attn_norm.weight | 0x24ff8f1e0 | 0x5000 |
| 266 | blk.29.attn_output.weight | 0x24ff941e0 | 0xb40000 |
| 267 | blk.29.attn_q.weight | 0x250ad41e0 | 0x898000 |
| 268 | blk.29.attn_v.weight | 0x25136c1e0 | 0x2d0000 |
| 269 | blk.29.ffn_down.weight | 0x25163c1e0 | 0x6e00000 |
| 270 | blk.29.ffn_gate.weight | 0x25843c1e0 | 0x44c0000 |
| 271 | blk.29.ffn_norm.weight | 0x25c8fc1e0 | 0x5000 |
| 272 | blk.29.ffn_up.weight | 0x25c9011e0 | 0x44c0000 |
| 273 | blk.30.attn_k.weight | 0x260dc11e0 | 0x226000 |
| 274 | blk.30.attn_norm.weight | 0x260fe71e0 | 0x5000 |
| 275 | blk.30.attn_output.weight | 0x260fec1e0 | 0xb40000 |
| 276 | blk.30.attn_q.weight | 0x261b2c1e0 | 0x898000 |
| 277 | blk.30.attn_v.weight | 0x2623c41e0 | 0x2d0000 |
| 278 | blk.30.ffn_down.weight | 0x2626941e0 | 0x6e00000 |
| 279 | blk.30.ffn_gate.weight | 0x2694941e0 | 0x44c0000 |
| 280 | blk.30.ffn_norm.weight | 0x26d9541e0 | 0x5000 |
| 281 | blk.30.ffn_up.weight | 0x26d9591e0 | 0x44c0000 |
| 282 | blk.31.attn_k.weight | 0x271e191e0 | 0x226000 |
| 283 | blk.31.attn_norm.weight | 0x27203f1e0 | 0x5000 |
| 284 | blk.31.attn_output.weight | 0x2720441e0 | 0xb40000 |
| 285 | blk.31.attn_q.weight | 0x272b841e0 | 0x898000 |
| 286 | blk.31.attn_v.weight | 0x27341c1e0 | 0x2d0000 |
| 287 | blk.31.ffn_down.weight | 0x2736ec1e0 | 0x6e00000 |
| 288 | blk.31.ffn_gate.weight | 0x27a4ec1e0 | 0x44c0000 |
| 289 | blk.31.ffn_norm.weight | 0x27e9ac1e0 | 0x5000 |
| 290 | blk.31.ffn_up.weight | 0x27e9b11e0 | 0x44c0000 |
| 291 | blk.32.attn_k.weight | 0x282e711e0 | 0x226000 |
| 292 | blk.32.attn_norm.weight | 0x2830971e0 | 0x5000 |
| 293 | blk.32.attn_output.weight | 0x28309c1e0 | 0xb40000 |
| 294 | blk.32.attn_q.weight | 0x283bdc1e0 | 0x898000 |
| 295 | blk.32.attn_v.weight | 0x2844741e0 | 0x2d0000 |
| 296 | blk.32.ffn_down.weight | 0x2847441e0 | 0x6e00000 |
| 297 | blk.32.ffn_gate.weight | 0x28b5441e0 | 0x44c0000 |
| 298 | blk.32.ffn_norm.weight | 0x28fa041e0 | 0x5000 |
| 299 | blk.32.ffn_up.weight | 0x28fa091e0 | 0x44c0000 |
| 300 | blk.33.attn_k.weight | 0x293ec91e0 | 0x226000 |
| 301 | blk.33.attn_norm.weight | 0x2940ef1e0 | 0x5000 |
| 302 | blk.33.attn_output.weight | 0x2940f41e0 | 0xb40000 |
| 303 | blk.33.attn_q.weight | 0x294c341e0 | 0x898000 |
| 304 | blk.33.attn_v.weight | 0x2954cc1e0 | 0x2d0000 |
| 305 | blk.33.ffn_down.weight | 0x29579c1e0 | 0x6e00000 |
| 306 | blk.33.ffn_gate.weight | 0x29c59c1e0 | 0x44c0000 |
| 307 | blk.33.ffn_norm.weight | 0x2a0a5c1e0 | 0x5000 |
| 308 | blk.33.ffn_up.weight | 0x2a0a611e0 | 0x44c0000 |
| 309 | blk.34.attn_k.weight | 0x2a4f211e0 | 0x226000 |
| 310 | blk.34.attn_norm.weight | 0x2a51471e0 | 0x5000 |
| 311 | blk.34.attn_output.weight | 0x2a514c1e0 | 0xb40000 |
| 312 | blk.34.attn_q.weight | 0x2a5c8c1e0 | 0x898000 |
| 313 | blk.34.attn_v.weight | 0x2a65241e0 | 0x2d0000 |
| 314 | blk.34.ffn_down.weight | 0x2a67f41e0 | 0x6e00000 |
| 315 | blk.34.ffn_gate.weight | 0x2ad5f41e0 | 0x44c0000 |
| 316 | blk.34.ffn_norm.weight | 0x2b1ab41e0 | 0x5000 |
| 317 | blk.34.ffn_up.weight | 0x2b1ab91e0 | 0x44c0000 |
| 318 | blk.35.attn_k.weight | 0x2b5f791e0 | 0x226000 |
| 319 | blk.35.attn_norm.weight | 0x2b619f1e0 | 0x5000 |
| 320 | blk.35.attn_output.weight | 0x2b61a41e0 | 0xb40000 |
| 321 | blk.35.attn_q.weight | 0x2b6ce41e0 | 0x898000 |
| 322 | blk.35.attn_v.weight | 0x2b757c1e0 | 0x2d0000 |
| 323 | blk.35.ffn_down.weight | 0x2b784c1e0 | 0x6e00000 |
| 324 | blk.35.ffn_gate.weight | 0x2be64c1e0 | 0x44c0000 |
| 325 | blk.35.ffn_norm.weight | 0x2c2b0c1e0 | 0x5000 |
| 326 | blk.35.ffn_up.weight | 0x2c2b111e0 | 0x44c0000 |
| 327 | blk.36.attn_k.weight | 0x2c6fd11e0 | 0x226000 |
| 328 | blk.36.attn_norm.weight | 0x2c71f71e0 | 0x5000 |
| 329 | blk.36.attn_output.weight | 0x2c71fc1e0 | 0xb40000 |
| 330 | blk.36.attn_q.weight | 0x2c7d3c1e0 | 0x898000 |
| 331 | blk.36.attn_v.weight | 0x2c85d41e0 | 0x2d0000 |
| 332 | blk.36.ffn_down.weight | 0x2c88a41e0 | 0x6e00000 |
| 333 | blk.36.ffn_gate.weight | 0x2cf6a41e0 | 0x44c0000 |
| 334 | blk.36.ffn_norm.weight | 0x2d3b641e0 | 0x5000 |
| 335 | blk.36.ffn_up.weight | 0x2d3b691e0 | 0x44c0000 |
| 336 | blk.37.attn_k.weight | 0x2d80291e0 | 0x226000 |
| 337 | blk.37.attn_norm.weight | 0x2d824f1e0 | 0x5000 |
| 338 | blk.37.attn_output.weight | 0x2d82541e0 | 0xb40000 |
| 339 | blk.37.attn_q.weight | 0x2d8d941e0 | 0x898000 |
| 340 | blk.37.attn_v.weight | 0x2d962c1e0 | 0x2d0000 |
| 341 | blk.37.ffn_down.weight | 0x2d98fc1e0 | 0x6e00000 |
| 342 | blk.37.ffn_gate.weight | 0x2e06fc1e0 | 0x44c0000 |
| 343 | blk.37.ffn_norm.weight | 0x2e4bbc1e0 | 0x5000 |
| 344 | blk.37.ffn_up.weight | 0x2e4bc11e0 | 0x44c0000 |
Base Tensor Group : ~1B Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 0 | output.weight | Output (W) | (~671M) 671088640 | 5120 x 131072 x 1 x 1 | Q4_K | 4.5000 |
| 1 | output_norm.weight | Output Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 2 | token_embd.weight | Token Embedding (W) | (~671M) 671088640 | 5120 x 131072 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in base: ( ~1B) 1342182400
- Percentage of total elements: 5.98%
- Bits per Weight (BPW) for base: 3.9689 bits
Block 0 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 3 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 4 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 5 | blk.0.attn_output.weight | Block 0 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 6 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 7 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 8 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 9 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 10 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 11 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.0: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.0: 4.8118 bits
Block 1 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 12 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 13 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 14 | blk.1.attn_output.weight | Block 1 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 15 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 16 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 17 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 18 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 19 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 20 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.1: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.1: 4.8118 bits
Block 2 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 21 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 22 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 23 | blk.2.attn_output.weight | Block 2 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 24 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 25 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 26 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 27 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 28 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 29 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.2: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.2: 4.8118 bits
Block 3 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 30 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 31 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 32 | blk.3.attn_output.weight | Block 3 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 33 | blk.3.attn_q.weight | Block 3 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 34 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 35 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 36 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 37 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 38 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.3: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.3: 4.8118 bits
Block 4 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 39 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 40 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 41 | blk.4.attn_output.weight | Block 4 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 42 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 43 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 44 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 45 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 46 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 47 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.4: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.4: 4.8118 bits
Block 5 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 48 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 49 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 50 | blk.5.attn_output.weight | Block 5 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 51 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 52 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 53 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 54 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 55 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 56 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.5: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.5: 4.8118 bits
Block 6 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 57 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 58 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 59 | blk.6.attn_output.weight | Block 6 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 60 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 61 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 62 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 63 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 64 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 65 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.6: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.6: 4.8118 bits
Block 7 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 66 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 67 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 68 | blk.7.attn_output.weight | Block 7 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 69 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 70 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 71 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 72 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 73 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 74 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.7: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.7: 4.8118 bits
Block 8 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 75 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 76 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 77 | blk.8.attn_output.weight | Block 8 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 78 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 79 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 80 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 81 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 82 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 83 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.8: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.8: 4.8118 bits
Block 9 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 84 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 85 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 86 | blk.9.attn_output.weight | Block 9 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 87 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 88 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 89 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 90 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 91 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 92 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.9: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.9: 4.8118 bits
Block 10 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 93 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 94 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 95 | blk.10.attn_output.weight | Block 10 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 96 | blk.10.attn_q.weight | Block 10 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 97 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 98 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 99 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 100 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 101 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.10: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.10: 4.8118 bits
Block 11 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 102 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 103 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 104 | blk.11.attn_output.weight | Block 11 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 105 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 106 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 107 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 108 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 109 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 110 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.11: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.11: 4.8118 bits
Block 12 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 111 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 112 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 113 | blk.12.attn_output.weight | Block 12 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 114 | blk.12.attn_q.weight | Block 12 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 115 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 116 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 117 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 118 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 119 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.12: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.12: 4.8118 bits
Block 13 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 120 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 121 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 122 | blk.13.attn_output.weight | Block 13 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 123 | blk.13.attn_q.weight | Block 13 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 124 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 125 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 126 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 127 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 128 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.13: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.13: 4.8118 bits
Block 14 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 129 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 130 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 131 | blk.14.attn_output.weight | Block 14 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 132 | blk.14.attn_q.weight | Block 14 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 133 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 134 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 135 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 136 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 137 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.14: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.14: 4.8118 bits
Block 15 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 138 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 139 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 140 | blk.15.attn_output.weight | Block 15 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 141 | blk.15.attn_q.weight | Block 15 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 142 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 143 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 144 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 145 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 146 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.15: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.15: 4.8118 bits
Block 16 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 147 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 148 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 149 | blk.16.attn_output.weight | Block 16 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 150 | blk.16.attn_q.weight | Block 16 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 151 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 152 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 153 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 154 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 155 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.16: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.16: 4.8118 bits
Block 17 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 156 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 157 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 158 | blk.17.attn_output.weight | Block 17 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 159 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 160 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 161 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 162 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 163 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 164 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.17: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.17: 4.7523 bits
Block 18 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 165 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 166 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 167 | blk.18.attn_output.weight | Block 18 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 168 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 169 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 170 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 171 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 172 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 173 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.18: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.18: 4.7523 bits
Block 19 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 174 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 175 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 176 | blk.19.attn_output.weight | Block 19 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 177 | blk.19.attn_q.weight | Block 19 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 178 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 179 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 180 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
| 181 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 182 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q4_K | 4.5000 |
- Total elements in blk.19: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.19: 4.8118 bits
Block 20 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 183 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 184 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 185 | blk.20.attn_output.weight | Block 20 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 186 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 187 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 188 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 189 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 190 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 191 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.20: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.20: 4.1108 bits
Block 21 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 192 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 193 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 194 | blk.21.attn_output.weight | Block 21 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 195 | blk.21.attn_q.weight | Block 21 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 196 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 197 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 198 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 199 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 200 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.21: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.21: 4.1703 bits
Block 22 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 201 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 202 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 203 | blk.22.attn_output.weight | Block 22 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 204 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 205 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 206 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 207 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 208 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 209 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.22: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.22: 4.1108 bits
Block 23 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 210 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 211 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 212 | blk.23.attn_output.weight | Block 23 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 213 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 214 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 215 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 216 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 217 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 218 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.23: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.23: 4.1108 bits
Block 24 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 219 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 220 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 221 | blk.24.attn_output.weight | Block 24 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 222 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 223 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 224 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 225 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 226 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 227 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.24: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.24: 4.1108 bits
Block 25 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 228 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 229 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 230 | blk.25.attn_output.weight | Block 25 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 231 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 232 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 233 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 234 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 235 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 236 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.25: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.25: 4.1108 bits
Block 26 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 237 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 238 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 239 | blk.26.attn_output.weight | Block 26 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 240 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 241 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 242 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 243 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 244 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 245 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.26: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.26: 4.1108 bits
Block 27 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 246 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 247 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 248 | blk.27.attn_output.weight | Block 27 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 249 | blk.27.attn_q.weight | Block 27 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 |
| 250 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 |
| 251 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 252 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 253 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 254 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.27: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.27: 4.1703 bits
Block 28 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 255 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 256 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 257 | blk.28.attn_output.weight | Block 28 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 258 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 259 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 260 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 261 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 262 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 263 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.28: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.28: 4.1108 bits
Block 29 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 264 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 265 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 266 | blk.29.attn_output.weight | Block 29 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 267 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 268 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 269 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 270 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 271 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 272 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.29: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.29: 4.1108 bits
Block 30 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 273 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 274 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 275 | blk.30.attn_output.weight | Block 30 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 276 | blk.30.attn_q.weight | Block 30 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 277 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 278 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 279 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 280 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 281 | blk.30.ffn_up.weight | Block 30 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.30: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.30: 4.1108 bits
Block 31 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 282 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 283 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 284 | blk.31.attn_output.weight | Block 31 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 285 | blk.31.attn_q.weight | Block 31 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 286 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 287 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 288 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 289 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 290 | blk.31.ffn_up.weight | Block 31 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.31: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.31: 4.1108 bits
Block 32 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 291 | blk.32.attn_k.weight | Block 32 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 292 | blk.32.attn_norm.weight | Block 32 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 293 | blk.32.attn_output.weight | Block 32 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 294 | blk.32.attn_q.weight | Block 32 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 295 | blk.32.attn_v.weight | Block 32 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 296 | blk.32.ffn_down.weight | Block 32 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 297 | blk.32.ffn_gate.weight | Block 32 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 298 | blk.32.ffn_norm.weight | Block 32 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 299 | blk.32.ffn_up.weight | Block 32 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.32: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.32: 4.1108 bits
Block 33 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 300 | blk.33.attn_k.weight | Block 33 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 301 | blk.33.attn_norm.weight | Block 33 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 302 | blk.33.attn_output.weight | Block 33 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 303 | blk.33.attn_q.weight | Block 33 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 304 | blk.33.attn_v.weight | Block 33 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 305 | blk.33.ffn_down.weight | Block 33 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 306 | blk.33.ffn_gate.weight | Block 33 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 307 | blk.33.ffn_norm.weight | Block 33 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 308 | blk.33.ffn_up.weight | Block 33 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.33: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.33: 4.1108 bits
Block 34 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 309 | blk.34.attn_k.weight | Block 34 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 310 | blk.34.attn_norm.weight | Block 34 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 311 | blk.34.attn_output.weight | Block 34 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 312 | blk.34.attn_q.weight | Block 34 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 313 | blk.34.attn_v.weight | Block 34 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 314 | blk.34.ffn_down.weight | Block 34 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 315 | blk.34.ffn_gate.weight | Block 34 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 316 | blk.34.ffn_norm.weight | Block 34 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 317 | blk.34.ffn_up.weight | Block 34 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.34: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.34: 4.1108 bits
Block 35 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 318 | blk.35.attn_k.weight | Block 35 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 319 | blk.35.attn_norm.weight | Block 35 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 320 | blk.35.attn_output.weight | Block 35 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 321 | blk.35.attn_q.weight | Block 35 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 322 | blk.35.attn_v.weight | Block 35 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 323 | blk.35.ffn_down.weight | Block 35 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 324 | blk.35.ffn_gate.weight | Block 35 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 325 | blk.35.ffn_norm.weight | Block 35 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 326 | blk.35.ffn_up.weight | Block 35 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.35: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.35: 4.1108 bits
Block 36 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 327 | blk.36.attn_k.weight | Block 36 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 328 | blk.36.attn_norm.weight | Block 36 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 329 | blk.36.attn_output.weight | Block 36 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 330 | blk.36.attn_q.weight | Block 36 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 331 | blk.36.attn_v.weight | Block 36 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 332 | blk.36.ffn_down.weight | Block 36 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 333 | blk.36.ffn_gate.weight | Block 36 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 334 | blk.36.ffn_norm.weight | Block 36 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 335 | blk.36.ffn_up.weight | Block 36 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.36: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.36: 4.1108 bits
Block 37 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 336 | blk.37.attn_k.weight | Block 37 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q3_K | 3.4375 |
| 337 | blk.37.attn_norm.weight | Block 37 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 338 | blk.37.attn_output.weight | Block 37 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | Q4_K | 4.5000 |
| 339 | blk.37.attn_q.weight | Block 37 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q3_K | 3.4375 |
| 340 | blk.37.attn_v.weight | Block 37 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q4_K | 4.5000 |
| 341 | blk.37.ffn_down.weight | Block 37 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q5_K | 5.5000 |
| 342 | blk.37.ffn_gate.weight | Block 37 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
| 343 | blk.37.ffn_norm.weight | Block 37 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 344 | blk.37.ffn_up.weight | Block 37 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q3_K | 3.4375 |
- Total elements in blk.37: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.37: 4.1108 bits
Total BPW for Mistral-Small-3.2-24B-Instruct-pruned-Q4_K_M.gguf: 4.4492 bits