# Mistral-Small-3.2-24B-Instruct-pruned-Q5_K_S.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 | [ ``, ``, ``, `[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 | 16 | | 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-Q5\_K\_S.gguf - GGUF Internal File Dump](#mistral-small-32-24b-instruct-pruned-q5_k_sgguf---gguf-internal-file-dump) - [Key Value Metadata Store](#key-value-metadata-store) - [Tensors Overview ~22B Elements](#tensors-overview-22b-elements) - [Tensor Data Offset](#tensor-data-offset) - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements) - [Block 0 Tensor Group : ~556M Elements](#block-0-tensor-group--556m-elements) - [Block 1 Tensor Group : ~556M Elements](#block-1-tensor-group--556m-elements) - [Block 2 Tensor Group : ~556M Elements](#block-2-tensor-group--556m-elements) - [Block 3 Tensor Group : ~556M Elements](#block-3-tensor-group--556m-elements) - [Block 4 Tensor Group : ~556M Elements](#block-4-tensor-group--556m-elements) - [Block 5 Tensor Group : ~556M Elements](#block-5-tensor-group--556m-elements) - [Block 6 Tensor Group : ~556M Elements](#block-6-tensor-group--556m-elements) - [Block 7 Tensor Group : ~556M Elements](#block-7-tensor-group--556m-elements) - [Block 8 Tensor Group : ~556M Elements](#block-8-tensor-group--556m-elements) - [Block 9 Tensor Group : ~556M Elements](#block-9-tensor-group--556m-elements) - [Block 10 Tensor Group : ~556M Elements](#block-10-tensor-group--556m-elements) - [Block 11 Tensor Group : ~556M Elements](#block-11-tensor-group--556m-elements) - [Block 12 Tensor Group : ~556M Elements](#block-12-tensor-group--556m-elements) - [Block 13 Tensor Group : ~556M Elements](#block-13-tensor-group--556m-elements) - [Block 14 Tensor Group : ~556M Elements](#block-14-tensor-group--556m-elements) - [Block 15 Tensor Group : ~556M Elements](#block-15-tensor-group--556m-elements) - [Block 16 Tensor Group : ~556M Elements](#block-16-tensor-group--556m-elements) - [Block 17 Tensor Group : ~556M Elements](#block-17-tensor-group--556m-elements) - [Block 18 Tensor Group : ~556M Elements](#block-18-tensor-group--556m-elements) - [Block 19 Tensor Group : ~556M Elements](#block-19-tensor-group--556m-elements) - [Block 20 Tensor Group : ~556M Elements](#block-20-tensor-group--556m-elements) - [Block 21 Tensor Group : ~556M Elements](#block-21-tensor-group--556m-elements) - [Block 22 Tensor Group : ~556M Elements](#block-22-tensor-group--556m-elements) - [Block 23 Tensor Group : ~556M Elements](#block-23-tensor-group--556m-elements) - [Block 24 Tensor Group : ~556M Elements](#block-24-tensor-group--556m-elements) - [Block 25 Tensor Group : ~556M Elements](#block-25-tensor-group--556m-elements) - [Block 26 Tensor Group : ~556M Elements](#block-26-tensor-group--556m-elements) - [Block 27 Tensor Group : ~556M Elements](#block-27-tensor-group--556m-elements) - [Block 28 Tensor Group : ~556M Elements](#block-28-tensor-group--556m-elements) - [Block 29 Tensor Group : ~556M Elements](#block-29-tensor-group--556m-elements) - [Block 30 Tensor Group : ~556M Elements](#block-30-tensor-group--556m-elements) - [Block 31 Tensor Group : ~556M Elements](#block-31-tensor-group--556m-elements) - [Block 32 Tensor Group : ~556M Elements](#block-32-tensor-group--556m-elements) - [Block 33 Tensor Group : ~556M Elements](#block-33-tensor-group--556m-elements) - [Block 34 Tensor Group : ~556M Elements](#block-34-tensor-group--556m-elements) - [Block 35 Tensor Group : ~556M Elements](#block-35-tensor-group--556m-elements) - [Block 36 Tensor Group : ~556M Elements](#block-36-tensor-group--556m-elements) - [Block 37 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 | 0x1b800000 | | 1 | output_norm.weight | 0x1bf841e0 | 0x5000 | | 2 | token_embd.weight | 0x1bf891e0 | 0x11300000 | | 3 | blk.0.attn_k.weight | 0x2d2891e0 | 0x370000 | | 4 | blk.0.attn_norm.weight | 0x2d5f91e0 | 0x5000 | | 5 | blk.0.attn_output.weight | 0x2d5fe1e0 | 0xdc0000 | | 6 | blk.0.attn_q.weight | 0x2e3be1e0 | 0xdc0000 | | 7 | blk.0.attn_v.weight | 0x2f17e1e0 | 0x370000 | | 8 | blk.0.ffn_down.weight | 0x2f4ee1e0 | 0x8340000 | | 9 | blk.0.ffn_gate.weight | 0x3782e1e0 | 0x6e00000 | | 10 | blk.0.ffn_norm.weight | 0x3e62e1e0 | 0x5000 | | 11 | blk.0.ffn_up.weight | 0x3e6331e0 | 0x6e00000 | | 12 | blk.1.attn_k.weight | 0x454331e0 | 0x370000 | | 13 | blk.1.attn_norm.weight | 0x457a31e0 | 0x5000 | | 14 | blk.1.attn_output.weight | 0x457a81e0 | 0xdc0000 | | 15 | blk.1.attn_q.weight | 0x465681e0 | 0xdc0000 | | 16 | blk.1.attn_v.weight | 0x473281e0 | 0x370000 | | 17 | blk.1.ffn_down.weight | 0x476981e0 | 0x8340000 | | 18 | blk.1.ffn_gate.weight | 0x4f9d81e0 | 0x6e00000 | | 19 | blk.1.ffn_norm.weight | 0x567d81e0 | 0x5000 | | 20 | blk.1.ffn_up.weight | 0x567dd1e0 | 0x6e00000 | | 21 | blk.2.attn_k.weight | 0x5d5dd1e0 | 0x370000 | | 22 | blk.2.attn_norm.weight | 0x5d94d1e0 | 0x5000 | | 23 | blk.2.attn_output.weight | 0x5d9521e0 | 0xdc0000 | | 24 | blk.2.attn_q.weight | 0x5e7121e0 | 0xdc0000 | | 25 | blk.2.attn_v.weight | 0x5f4d21e0 | 0x370000 | | 26 | blk.2.ffn_down.weight | 0x5f8421e0 | 0x8340000 | | 27 | blk.2.ffn_gate.weight | 0x67b821e0 | 0x6e00000 | | 28 | blk.2.ffn_norm.weight | 0x6e9821e0 | 0x5000 | | 29 | blk.2.ffn_up.weight | 0x6e9871e0 | 0x6e00000 | | 30 | blk.3.attn_k.weight | 0x757871e0 | 0x2d0000 | | 31 | blk.3.attn_norm.weight | 0x75a571e0 | 0x5000 | | 32 | blk.3.attn_output.weight | 0x75a5c1e0 | 0xdc0000 | | 33 | blk.3.attn_q.weight | 0x7681c1e0 | 0xb40000 | | 34 | blk.3.attn_v.weight | 0x7735c1e0 | 0x370000 | | 35 | blk.3.ffn_down.weight | 0x776cc1e0 | 0x8340000 | | 36 | blk.3.ffn_gate.weight | 0x7fa0c1e0 | 0x6e00000 | | 37 | blk.3.ffn_norm.weight | 0x8680c1e0 | 0x5000 | | 38 | blk.3.ffn_up.weight | 0x868111e0 | 0x6e00000 | | 39 | blk.4.attn_k.weight | 0x8d6111e0 | 0x370000 | | 40 | blk.4.attn_norm.weight | 0x8d9811e0 | 0x5000 | | 41 | blk.4.attn_output.weight | 0x8d9861e0 | 0xdc0000 | | 42 | blk.4.attn_q.weight | 0x8e7461e0 | 0xdc0000 | | 43 | blk.4.attn_v.weight | 0x8f5061e0 | 0x370000 | | 44 | blk.4.ffn_down.weight | 0x8f8761e0 | 0x8340000 | | 45 | blk.4.ffn_gate.weight | 0x97bb61e0 | 0x6e00000 | | 46 | blk.4.ffn_norm.weight | 0x9e9b61e0 | 0x5000 | | 47 | blk.4.ffn_up.weight | 0x9e9bb1e0 | 0x6e00000 | | 48 | blk.5.attn_k.weight | 0xa57bb1e0 | 0x370000 | | 49 | blk.5.attn_norm.weight | 0xa5b2b1e0 | 0x5000 | | 50 | blk.5.attn_output.weight | 0xa5b301e0 | 0xdc0000 | | 51 | blk.5.attn_q.weight | 0xa68f01e0 | 0xdc0000 | | 52 | blk.5.attn_v.weight | 0xa76b01e0 | 0x370000 | | 53 | blk.5.ffn_down.weight | 0xa7a201e0 | 0x8340000 | | 54 | blk.5.ffn_gate.weight | 0xafd601e0 | 0x6e00000 | | 55 | blk.5.ffn_norm.weight | 0xb6b601e0 | 0x5000 | | 56 | blk.5.ffn_up.weight | 0xb6b651e0 | 0x6e00000 | | 57 | blk.6.attn_k.weight | 0xbd9651e0 | 0x370000 | | 58 | blk.6.attn_norm.weight | 0xbdcd51e0 | 0x5000 | | 59 | blk.6.attn_output.weight | 0xbdcda1e0 | 0xdc0000 | | 60 | blk.6.attn_q.weight | 0xbea9a1e0 | 0xdc0000 | | 61 | blk.6.attn_v.weight | 0xbf85a1e0 | 0x370000 | | 62 | blk.6.ffn_down.weight | 0xbfbca1e0 | 0x8340000 | | 63 | blk.6.ffn_gate.weight | 0xc7f0a1e0 | 0x6e00000 | | 64 | blk.6.ffn_norm.weight | 0xced0a1e0 | 0x5000 | | 65 | blk.6.ffn_up.weight | 0xced0f1e0 | 0x6e00000 | | 66 | blk.7.attn_k.weight | 0xd5b0f1e0 | 0x370000 | | 67 | blk.7.attn_norm.weight | 0xd5e7f1e0 | 0x5000 | | 68 | blk.7.attn_output.weight | 0xd5e841e0 | 0xdc0000 | | 69 | blk.7.attn_q.weight | 0xd6c441e0 | 0xdc0000 | | 70 | blk.7.attn_v.weight | 0xd7a041e0 | 0x370000 | | 71 | blk.7.ffn_down.weight | 0xd7d741e0 | 0x8340000 | | 72 | blk.7.ffn_gate.weight | 0xe00b41e0 | 0x6e00000 | | 73 | blk.7.ffn_norm.weight | 0xe6eb41e0 | 0x5000 | | 74 | blk.7.ffn_up.weight | 0xe6eb91e0 | 0x6e00000 | | 75 | blk.8.attn_k.weight | 0xedcb91e0 | 0x370000 | | 76 | blk.8.attn_norm.weight | 0xee0291e0 | 0x5000 | | 77 | blk.8.attn_output.weight | 0xee02e1e0 | 0xdc0000 | | 78 | blk.8.attn_q.weight | 0xeedee1e0 | 0xdc0000 | | 79 | blk.8.attn_v.weight | 0xefbae1e0 | 0x370000 | | 80 | blk.8.ffn_down.weight | 0xeff1e1e0 | 0x8340000 | | 81 | blk.8.ffn_gate.weight | 0xf825e1e0 | 0x6e00000 | | 82 | blk.8.ffn_norm.weight | 0xff05e1e0 | 0x5000 | | 83 | blk.8.ffn_up.weight | 0xff0631e0 | 0x6e00000 | | 84 | blk.9.attn_k.weight | 0x105e631e0 | 0x370000 | | 85 | blk.9.attn_norm.weight | 0x1061d31e0 | 0x5000 | | 86 | blk.9.attn_output.weight | 0x1061d81e0 | 0xdc0000 | | 87 | blk.9.attn_q.weight | 0x106f981e0 | 0xdc0000 | | 88 | blk.9.attn_v.weight | 0x107d581e0 | 0x370000 | | 89 | blk.9.ffn_down.weight | 0x1080c81e0 | 0x8340000 | | 90 | blk.9.ffn_gate.weight | 0x1104081e0 | 0x6e00000 | | 91 | blk.9.ffn_norm.weight | 0x1172081e0 | 0x5000 | | 92 | blk.9.ffn_up.weight | 0x11720d1e0 | 0x6e00000 | | 93 | blk.10.attn_k.weight | 0x11e00d1e0 | 0x2d0000 | | 94 | blk.10.attn_norm.weight | 0x11e2dd1e0 | 0x5000 | | 95 | blk.10.attn_output.weight | 0x11e2e21e0 | 0xdc0000 | | 96 | blk.10.attn_q.weight | 0x11f0a21e0 | 0xb40000 | | 97 | blk.10.attn_v.weight | 0x11fbe21e0 | 0x370000 | | 98 | blk.10.ffn_down.weight | 0x11ff521e0 | 0x8340000 | | 99 | blk.10.ffn_gate.weight | 0x1282921e0 | 0x5a00000 | | 100 | blk.10.ffn_norm.weight | 0x12dc921e0 | 0x5000 | | 101 | blk.10.ffn_up.weight | 0x12dc971e0 | 0x5a00000 | | 102 | blk.11.attn_k.weight | 0x1336971e0 | 0x370000 | | 103 | blk.11.attn_norm.weight | 0x133a071e0 | 0x5000 | | 104 | blk.11.attn_output.weight | 0x133a0c1e0 | 0xdc0000 | | 105 | blk.11.attn_q.weight | 0x1347cc1e0 | 0xdc0000 | | 106 | blk.11.attn_v.weight | 0x13558c1e0 | 0x370000 | | 107 | blk.11.ffn_down.weight | 0x1358fc1e0 | 0x8340000 | | 108 | blk.11.ffn_gate.weight | 0x13dc3c1e0 | 0x5a00000 | | 109 | blk.11.ffn_norm.weight | 0x14363c1e0 | 0x5000 | | 110 | blk.11.ffn_up.weight | 0x1436411e0 | 0x5a00000 | | 111 | blk.12.attn_k.weight | 0x1490411e0 | 0x2d0000 | | 112 | blk.12.attn_norm.weight | 0x1493111e0 | 0x5000 | | 113 | blk.12.attn_output.weight | 0x1493161e0 | 0xdc0000 | | 114 | blk.12.attn_q.weight | 0x14a0d61e0 | 0xb40000 | | 115 | blk.12.attn_v.weight | 0x14ac161e0 | 0x370000 | | 116 | blk.12.ffn_down.weight | 0x14af861e0 | 0x8340000 | | 117 | blk.12.ffn_gate.weight | 0x1532c61e0 | 0x5a00000 | | 118 | blk.12.ffn_norm.weight | 0x158cc61e0 | 0x5000 | | 119 | blk.12.ffn_up.weight | 0x158ccb1e0 | 0x5a00000 | | 120 | blk.13.attn_k.weight | 0x15e6cb1e0 | 0x2d0000 | | 121 | blk.13.attn_norm.weight | 0x15e99b1e0 | 0x5000 | | 122 | blk.13.attn_output.weight | 0x15e9a01e0 | 0xdc0000 | | 123 | blk.13.attn_q.weight | 0x15f7601e0 | 0xb40000 | | 124 | blk.13.attn_v.weight | 0x1602a01e0 | 0x370000 | | 125 | blk.13.ffn_down.weight | 0x1606101e0 | 0x8340000 | | 126 | blk.13.ffn_gate.weight | 0x1689501e0 | 0x5a00000 | | 127 | blk.13.ffn_norm.weight | 0x16e3501e0 | 0x5000 | | 128 | blk.13.ffn_up.weight | 0x16e3551e0 | 0x5a00000 | | 129 | blk.14.attn_k.weight | 0x173d551e0 | 0x2d0000 | | 130 | blk.14.attn_norm.weight | 0x1740251e0 | 0x5000 | | 131 | blk.14.attn_output.weight | 0x17402a1e0 | 0xdc0000 | | 132 | blk.14.attn_q.weight | 0x174dea1e0 | 0xb40000 | | 133 | blk.14.attn_v.weight | 0x17592a1e0 | 0x370000 | | 134 | blk.14.ffn_down.weight | 0x175c9a1e0 | 0x8340000 | | 135 | blk.14.ffn_gate.weight | 0x17dfda1e0 | 0x5a00000 | | 136 | blk.14.ffn_norm.weight | 0x1839da1e0 | 0x5000 | | 137 | blk.14.ffn_up.weight | 0x1839df1e0 | 0x5a00000 | | 138 | blk.15.attn_k.weight | 0x1893df1e0 | 0x2d0000 | | 139 | blk.15.attn_norm.weight | 0x1896af1e0 | 0x5000 | | 140 | blk.15.attn_output.weight | 0x1896b41e0 | 0xdc0000 | | 141 | blk.15.attn_q.weight | 0x18a4741e0 | 0xb40000 | | 142 | blk.15.attn_v.weight | 0x18afb41e0 | 0x370000 | | 143 | blk.15.ffn_down.weight | 0x18b3241e0 | 0x8340000 | | 144 | blk.15.ffn_gate.weight | 0x1936641e0 | 0x5a00000 | | 145 | blk.15.ffn_norm.weight | 0x1990641e0 | 0x5000 | | 146 | blk.15.ffn_up.weight | 0x1990691e0 | 0x5a00000 | | 147 | blk.16.attn_k.weight | 0x19ea691e0 | 0x2d0000 | | 148 | blk.16.attn_norm.weight | 0x19ed391e0 | 0x5000 | | 149 | blk.16.attn_output.weight | 0x19ed3e1e0 | 0xdc0000 | | 150 | blk.16.attn_q.weight | 0x19fafe1e0 | 0xb40000 | | 151 | blk.16.attn_v.weight | 0x1a063e1e0 | 0x370000 | | 152 | blk.16.ffn_down.weight | 0x1a09ae1e0 | 0x8340000 | | 153 | blk.16.ffn_gate.weight | 0x1a8cee1e0 | 0x5a00000 | | 154 | blk.16.ffn_norm.weight | 0x1ae6ee1e0 | 0x5000 | | 155 | blk.16.ffn_up.weight | 0x1ae6f31e0 | 0x5a00000 | | 156 | blk.17.attn_k.weight | 0x1b40f31e0 | 0x2d0000 | | 157 | blk.17.attn_norm.weight | 0x1b43c31e0 | 0x5000 | | 158 | blk.17.attn_output.weight | 0x1b43c81e0 | 0xdc0000 | | 159 | blk.17.attn_q.weight | 0x1b51881e0 | 0xb40000 | | 160 | blk.17.attn_v.weight | 0x1b5cc81e0 | 0x370000 | | 161 | blk.17.ffn_down.weight | 0x1b60381e0 | 0x8340000 | | 162 | blk.17.ffn_gate.weight | 0x1be3781e0 | 0x5a00000 | | 163 | blk.17.ffn_norm.weight | 0x1c3d781e0 | 0x5000 | | 164 | blk.17.ffn_up.weight | 0x1c3d7d1e0 | 0x5a00000 | | 165 | blk.18.attn_k.weight | 0x1c977d1e0 | 0x2d0000 | | 166 | blk.18.attn_norm.weight | 0x1c9a4d1e0 | 0x5000 | | 167 | blk.18.attn_output.weight | 0x1c9a521e0 | 0xdc0000 | | 168 | blk.18.attn_q.weight | 0x1ca8121e0 | 0xb40000 | | 169 | blk.18.attn_v.weight | 0x1cb3521e0 | 0x370000 | | 170 | blk.18.ffn_down.weight | 0x1cb6c21e0 | 0x8340000 | | 171 | blk.18.ffn_gate.weight | 0x1d3a021e0 | 0x5a00000 | | 172 | blk.18.ffn_norm.weight | 0x1d94021e0 | 0x5000 | | 173 | blk.18.ffn_up.weight | 0x1d94071e0 | 0x5a00000 | | 174 | blk.19.attn_k.weight | 0x1dee071e0 | 0x2d0000 | | 175 | blk.19.attn_norm.weight | 0x1df0d71e0 | 0x5000 | | 176 | blk.19.attn_output.weight | 0x1df0dc1e0 | 0xdc0000 | | 177 | blk.19.attn_q.weight | 0x1dfe9c1e0 | 0xb40000 | | 178 | blk.19.attn_v.weight | 0x1e09dc1e0 | 0x370000 | | 179 | blk.19.ffn_down.weight | 0x1e0d4c1e0 | 0x8340000 | | 180 | blk.19.ffn_gate.weight | 0x1e908c1e0 | 0x5a00000 | | 181 | blk.19.ffn_norm.weight | 0x1eea8c1e0 | 0x5000 | | 182 | blk.19.ffn_up.weight | 0x1eea911e0 | 0x5a00000 | | 183 | blk.20.attn_k.weight | 0x1f44911e0 | 0x2d0000 | | 184 | blk.20.attn_norm.weight | 0x1f47611e0 | 0x5000 | | 185 | blk.20.attn_output.weight | 0x1f47661e0 | 0xdc0000 | | 186 | blk.20.attn_q.weight | 0x1f55261e0 | 0xb40000 | | 187 | blk.20.attn_v.weight | 0x1f60661e0 | 0x370000 | | 188 | blk.20.ffn_down.weight | 0x1f63d61e0 | 0x6e00000 | | 189 | blk.20.ffn_gate.weight | 0x1fd1d61e0 | 0x5a00000 | | 190 | blk.20.ffn_norm.weight | 0x202bd61e0 | 0x5000 | | 191 | blk.20.ffn_up.weight | 0x202bdb1e0 | 0x5a00000 | | 192 | blk.21.attn_k.weight | 0x2085db1e0 | 0x2d0000 | | 193 | blk.21.attn_norm.weight | 0x2088ab1e0 | 0x5000 | | 194 | blk.21.attn_output.weight | 0x2088b01e0 | 0xdc0000 | | 195 | blk.21.attn_q.weight | 0x2096701e0 | 0xb40000 | | 196 | blk.21.attn_v.weight | 0x20a1b01e0 | 0x370000 | | 197 | blk.21.ffn_down.weight | 0x20a5201e0 | 0x6e00000 | | 198 | blk.21.ffn_gate.weight | 0x2113201e0 | 0x5a00000 | | 199 | blk.21.ffn_norm.weight | 0x216d201e0 | 0x5000 | | 200 | blk.21.ffn_up.weight | 0x216d251e0 | 0x5a00000 | | 201 | blk.22.attn_k.weight | 0x21c7251e0 | 0x2d0000 | | 202 | blk.22.attn_norm.weight | 0x21c9f51e0 | 0x5000 | | 203 | blk.22.attn_output.weight | 0x21c9fa1e0 | 0xdc0000 | | 204 | blk.22.attn_q.weight | 0x21d7ba1e0 | 0xb40000 | | 205 | blk.22.attn_v.weight | 0x21e2fa1e0 | 0x370000 | | 206 | blk.22.ffn_down.weight | 0x21e66a1e0 | 0x6e00000 | | 207 | blk.22.ffn_gate.weight | 0x22546a1e0 | 0x5a00000 | | 208 | blk.22.ffn_norm.weight | 0x22ae6a1e0 | 0x5000 | | 209 | blk.22.ffn_up.weight | 0x22ae6f1e0 | 0x5a00000 | | 210 | blk.23.attn_k.weight | 0x23086f1e0 | 0x2d0000 | | 211 | blk.23.attn_norm.weight | 0x230b3f1e0 | 0x5000 | | 212 | blk.23.attn_output.weight | 0x230b441e0 | 0xdc0000 | | 213 | blk.23.attn_q.weight | 0x2319041e0 | 0xb40000 | | 214 | blk.23.attn_v.weight | 0x2324441e0 | 0x370000 | | 215 | blk.23.ffn_down.weight | 0x2327b41e0 | 0x6e00000 | | 216 | blk.23.ffn_gate.weight | 0x2395b41e0 | 0x5a00000 | | 217 | blk.23.ffn_norm.weight | 0x23efb41e0 | 0x5000 | | 218 | blk.23.ffn_up.weight | 0x23efb91e0 | 0x5a00000 | | 219 | blk.24.attn_k.weight | 0x2449b91e0 | 0x2d0000 | | 220 | blk.24.attn_norm.weight | 0x244c891e0 | 0x5000 | | 221 | blk.24.attn_output.weight | 0x244c8e1e0 | 0xdc0000 | | 222 | blk.24.attn_q.weight | 0x245a4e1e0 | 0xb40000 | | 223 | blk.24.attn_v.weight | 0x24658e1e0 | 0x370000 | | 224 | blk.24.ffn_down.weight | 0x2468fe1e0 | 0x6e00000 | | 225 | blk.24.ffn_gate.weight | 0x24d6fe1e0 | 0x5a00000 | | 226 | blk.24.ffn_norm.weight | 0x2530fe1e0 | 0x5000 | | 227 | blk.24.ffn_up.weight | 0x2531031e0 | 0x5a00000 | | 228 | blk.25.attn_k.weight | 0x258b031e0 | 0x2d0000 | | 229 | blk.25.attn_norm.weight | 0x258dd31e0 | 0x5000 | | 230 | blk.25.attn_output.weight | 0x258dd81e0 | 0xdc0000 | | 231 | blk.25.attn_q.weight | 0x259b981e0 | 0xb40000 | | 232 | blk.25.attn_v.weight | 0x25a6d81e0 | 0x370000 | | 233 | blk.25.ffn_down.weight | 0x25aa481e0 | 0x6e00000 | | 234 | blk.25.ffn_gate.weight | 0x2618481e0 | 0x5a00000 | | 235 | blk.25.ffn_norm.weight | 0x2672481e0 | 0x5000 | | 236 | blk.25.ffn_up.weight | 0x26724d1e0 | 0x5a00000 | | 237 | blk.26.attn_k.weight | 0x26cc4d1e0 | 0x2d0000 | | 238 | blk.26.attn_norm.weight | 0x26cf1d1e0 | 0x5000 | | 239 | blk.26.attn_output.weight | 0x26cf221e0 | 0xdc0000 | | 240 | blk.26.attn_q.weight | 0x26dce21e0 | 0xb40000 | | 241 | blk.26.attn_v.weight | 0x26e8221e0 | 0x370000 | | 242 | blk.26.ffn_down.weight | 0x26eb921e0 | 0x6e00000 | | 243 | blk.26.ffn_gate.weight | 0x2759921e0 | 0x5a00000 | | 244 | blk.26.ffn_norm.weight | 0x27b3921e0 | 0x5000 | | 245 | blk.26.ffn_up.weight | 0x27b3971e0 | 0x5a00000 | | 246 | blk.27.attn_k.weight | 0x280d971e0 | 0x2d0000 | | 247 | blk.27.attn_norm.weight | 0x2810671e0 | 0x5000 | | 248 | blk.27.attn_output.weight | 0x28106c1e0 | 0xdc0000 | | 249 | blk.27.attn_q.weight | 0x281e2c1e0 | 0xb40000 | | 250 | blk.27.attn_v.weight | 0x28296c1e0 | 0x370000 | | 251 | blk.27.ffn_down.weight | 0x282cdc1e0 | 0x6e00000 | | 252 | blk.27.ffn_gate.weight | 0x289adc1e0 | 0x5a00000 | | 253 | blk.27.ffn_norm.weight | 0x28f4dc1e0 | 0x5000 | | 254 | blk.27.ffn_up.weight | 0x28f4e11e0 | 0x5a00000 | | 255 | blk.28.attn_k.weight | 0x294ee11e0 | 0x2d0000 | | 256 | blk.28.attn_norm.weight | 0x2951b11e0 | 0x5000 | | 257 | blk.28.attn_output.weight | 0x2951b61e0 | 0xdc0000 | | 258 | blk.28.attn_q.weight | 0x295f761e0 | 0xb40000 | | 259 | blk.28.attn_v.weight | 0x296ab61e0 | 0x370000 | | 260 | blk.28.ffn_down.weight | 0x296e261e0 | 0x6e00000 | | 261 | blk.28.ffn_gate.weight | 0x29dc261e0 | 0x5a00000 | | 262 | blk.28.ffn_norm.weight | 0x2a36261e0 | 0x5000 | | 263 | blk.28.ffn_up.weight | 0x2a362b1e0 | 0x5a00000 | | 264 | blk.29.attn_k.weight | 0x2a902b1e0 | 0x2d0000 | | 265 | blk.29.attn_norm.weight | 0x2a92fb1e0 | 0x5000 | | 266 | blk.29.attn_output.weight | 0x2a93001e0 | 0xdc0000 | | 267 | blk.29.attn_q.weight | 0x2aa0c01e0 | 0xb40000 | | 268 | blk.29.attn_v.weight | 0x2aac001e0 | 0x370000 | | 269 | blk.29.ffn_down.weight | 0x2aaf701e0 | 0x6e00000 | | 270 | blk.29.ffn_gate.weight | 0x2b1d701e0 | 0x5a00000 | | 271 | blk.29.ffn_norm.weight | 0x2b77701e0 | 0x5000 | | 272 | blk.29.ffn_up.weight | 0x2b77751e0 | 0x5a00000 | | 273 | blk.30.attn_k.weight | 0x2bd1751e0 | 0x2d0000 | | 274 | blk.30.attn_norm.weight | 0x2bd4451e0 | 0x5000 | | 275 | blk.30.attn_output.weight | 0x2bd44a1e0 | 0xdc0000 | | 276 | blk.30.attn_q.weight | 0x2be20a1e0 | 0xb40000 | | 277 | blk.30.attn_v.weight | 0x2bed4a1e0 | 0x370000 | | 278 | blk.30.ffn_down.weight | 0x2bf0ba1e0 | 0x6e00000 | | 279 | blk.30.ffn_gate.weight | 0x2c5eba1e0 | 0x5a00000 | | 280 | blk.30.ffn_norm.weight | 0x2cb8ba1e0 | 0x5000 | | 281 | blk.30.ffn_up.weight | 0x2cb8bf1e0 | 0x5a00000 | | 282 | blk.31.attn_k.weight | 0x2d12bf1e0 | 0x2d0000 | | 283 | blk.31.attn_norm.weight | 0x2d158f1e0 | 0x5000 | | 284 | blk.31.attn_output.weight | 0x2d15941e0 | 0xdc0000 | | 285 | blk.31.attn_q.weight | 0x2d23541e0 | 0xb40000 | | 286 | blk.31.attn_v.weight | 0x2d2e941e0 | 0x370000 | | 287 | blk.31.ffn_down.weight | 0x2d32041e0 | 0x6e00000 | | 288 | blk.31.ffn_gate.weight | 0x2da0041e0 | 0x5a00000 | | 289 | blk.31.ffn_norm.weight | 0x2dfa041e0 | 0x5000 | | 290 | blk.31.ffn_up.weight | 0x2dfa091e0 | 0x5a00000 | | 291 | blk.32.attn_k.weight | 0x2e54091e0 | 0x2d0000 | | 292 | blk.32.attn_norm.weight | 0x2e56d91e0 | 0x5000 | | 293 | blk.32.attn_output.weight | 0x2e56de1e0 | 0xdc0000 | | 294 | blk.32.attn_q.weight | 0x2e649e1e0 | 0xb40000 | | 295 | blk.32.attn_v.weight | 0x2e6fde1e0 | 0x370000 | | 296 | blk.32.ffn_down.weight | 0x2e734e1e0 | 0x6e00000 | | 297 | blk.32.ffn_gate.weight | 0x2ee14e1e0 | 0x5a00000 | | 298 | blk.32.ffn_norm.weight | 0x2f3b4e1e0 | 0x5000 | | 299 | blk.32.ffn_up.weight | 0x2f3b531e0 | 0x5a00000 | | 300 | blk.33.attn_k.weight | 0x2f95531e0 | 0x2d0000 | | 301 | blk.33.attn_norm.weight | 0x2f98231e0 | 0x5000 | | 302 | blk.33.attn_output.weight | 0x2f98281e0 | 0xdc0000 | | 303 | blk.33.attn_q.weight | 0x2fa5e81e0 | 0xb40000 | | 304 | blk.33.attn_v.weight | 0x2fb1281e0 | 0x370000 | | 305 | blk.33.ffn_down.weight | 0x2fb4981e0 | 0x6e00000 | | 306 | blk.33.ffn_gate.weight | 0x3022981e0 | 0x5a00000 | | 307 | blk.33.ffn_norm.weight | 0x307c981e0 | 0x5000 | | 308 | blk.33.ffn_up.weight | 0x307c9d1e0 | 0x5a00000 | | 309 | blk.34.attn_k.weight | 0x30d69d1e0 | 0x2d0000 | | 310 | blk.34.attn_norm.weight | 0x30d96d1e0 | 0x5000 | | 311 | blk.34.attn_output.weight | 0x30d9721e0 | 0xdc0000 | | 312 | blk.34.attn_q.weight | 0x30e7321e0 | 0xb40000 | | 313 | blk.34.attn_v.weight | 0x30f2721e0 | 0x370000 | | 314 | blk.34.ffn_down.weight | 0x30f5e21e0 | 0x6e00000 | | 315 | blk.34.ffn_gate.weight | 0x3163e21e0 | 0x5a00000 | | 316 | blk.34.ffn_norm.weight | 0x31bde21e0 | 0x5000 | | 317 | blk.34.ffn_up.weight | 0x31bde71e0 | 0x5a00000 | | 318 | blk.35.attn_k.weight | 0x3217e71e0 | 0x2d0000 | | 319 | blk.35.attn_norm.weight | 0x321ab71e0 | 0x5000 | | 320 | blk.35.attn_output.weight | 0x321abc1e0 | 0xdc0000 | | 321 | blk.35.attn_q.weight | 0x32287c1e0 | 0xb40000 | | 322 | blk.35.attn_v.weight | 0x3233bc1e0 | 0x370000 | | 323 | blk.35.ffn_down.weight | 0x32372c1e0 | 0x6e00000 | | 324 | blk.35.ffn_gate.weight | 0x32a52c1e0 | 0x5a00000 | | 325 | blk.35.ffn_norm.weight | 0x32ff2c1e0 | 0x5000 | | 326 | blk.35.ffn_up.weight | 0x32ff311e0 | 0x5a00000 | | 327 | blk.36.attn_k.weight | 0x3359311e0 | 0x2d0000 | | 328 | blk.36.attn_norm.weight | 0x335c011e0 | 0x5000 | | 329 | blk.36.attn_output.weight | 0x335c061e0 | 0xdc0000 | | 330 | blk.36.attn_q.weight | 0x3369c61e0 | 0xb40000 | | 331 | blk.36.attn_v.weight | 0x3375061e0 | 0x370000 | | 332 | blk.36.ffn_down.weight | 0x3378761e0 | 0x6e00000 | | 333 | blk.36.ffn_gate.weight | 0x33e6761e0 | 0x5a00000 | | 334 | blk.36.ffn_norm.weight | 0x3440761e0 | 0x5000 | | 335 | blk.36.ffn_up.weight | 0x34407b1e0 | 0x5a00000 | | 336 | blk.37.attn_k.weight | 0x349a7b1e0 | 0x2d0000 | | 337 | blk.37.attn_norm.weight | 0x349d4b1e0 | 0x5000 | | 338 | blk.37.attn_output.weight | 0x349d501e0 | 0xdc0000 | | 339 | blk.37.attn_q.weight | 0x34ab101e0 | 0xb40000 | | 340 | blk.37.attn_v.weight | 0x34b6501e0 | 0x370000 | | 341 | blk.37.ffn_down.weight | 0x34b9c01e0 | 0x6e00000 | | 342 | blk.37.ffn_gate.weight | 0x3527c01e0 | 0x5a00000 | | 343 | blk.37.ffn_norm.weight | 0x3581c01e0 | 0x5000 | | 344 | blk.37.ffn_up.weight | 0x3581c51e0 | 0x5a00000 | ### 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 | Q5_K | 5.5000 | | 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: 4.4689 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 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | | 6 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 9 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | - Total elements in blk.0: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.0: 5.8212 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 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | | 15 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 18 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | - Total elements in blk.1: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.1: 5.8212 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 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | | 24 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 27 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | - Total elements in blk.2: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.2: 5.8212 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 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 36 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | - Total elements in blk.3: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.3: 5.7741 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 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | | 42 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 45 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | - Total elements in blk.4: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.4: 5.8212 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 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | | 51 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 54 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | - Total elements in blk.5: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.5: 5.8212 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 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | | 60 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 63 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | - Total elements in blk.6: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.6: 5.8212 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 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | | 69 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 72 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | - Total elements in blk.7: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.7: 5.8212 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 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | | 78 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 81 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | - Total elements in blk.8: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.8: 5.8212 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 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | | 87 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 90 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | - Total elements in blk.9: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.9: 5.8212 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 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 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: 5.1703 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 | Q5_K | 5.5000 | | 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 | Q5_K | 5.5000 | | 105 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 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: 5.2175 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 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 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: 5.1703 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 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 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: 5.1703 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 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 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: 5.1703 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 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 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: 5.1703 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 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 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: 5.1703 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 159 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 160 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 161 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K | 6.5625 | | 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: 5.1703 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 168 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 169 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 170 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | Q6_K | 6.5625 | | 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: 5.1703 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 | Q5_K | 5.5000 | | 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 | Q6_K | 6.5625 | | 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: 5.1703 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 186 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 187 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.20: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.20: 4.8496 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 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.21: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.21: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 204 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 205 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.22: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.22: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 213 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 214 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.23: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.23: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 222 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 223 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.24: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.24: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 231 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 232 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.25: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.25: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 240 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 241 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.26: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.26: 4.8496 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 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.27: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.27: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 258 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 259 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.28: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.28: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 267 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 268 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.29: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.29: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 276 | blk.30.attn_q.weight | Block 30 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 277 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.30: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.30: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 285 | blk.31.attn_q.weight | Block 31 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 286 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.31: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.31: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 294 | blk.32.attn_q.weight | Block 32 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 295 | blk.32.attn_v.weight | Block 32 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.32: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.32: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 303 | blk.33.attn_q.weight | Block 33 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 304 | blk.33.attn_v.weight | Block 33 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.33: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.33: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 312 | blk.34.attn_q.weight | Block 34 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 313 | blk.34.attn_v.weight | Block 34 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.34: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.34: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 321 | blk.35.attn_q.weight | Block 35 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 322 | blk.35.attn_v.weight | Block 35 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.35: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.35: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 330 | blk.36.attn_q.weight | Block 36 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 331 | blk.36.attn_v.weight | Block 36 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.36: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.36: 4.8496 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 | Q4_K | 4.5000 | | 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 | Q5_K | 5.5000 | | 339 | blk.37.attn_q.weight | Block 37 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | Q4_K | 4.5000 | | 340 | blk.37.attn_v.weight | Block 37 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | Q5_K | 5.5000 | | 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 | Q4_K | 4.5000 | | 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 | Q4_K | 4.5000 | - Total elements in blk.37: (~556M) 555755520 - Percentage of total elements: 2.47% - Bits per Weight (BPW) for blk.37: 4.8496 bits Total BPW for Mistral-Small-3.2-24B-Instruct-pruned-Q5_K_S.gguf: 5.1466 bits