# Hammer2.1-7b-Q5_K_S.gguf - GGUF Internal File Dump
- Endian: LITTLE endian
## Key Value Metadata Store
There are 36 key-value pairs in this file
| POS | TYPE | Count | Key | Value |
|----:|:---------|-------:|:-------------------------------------------|:--------------------------------------------------------------------|
| 1 | UINT32 | 1 | GGUF.version | 3 |
| 2 | UINT64 | 1 | GGUF.tensor_count | 339 |
| 3 | UINT64 | 1 | GGUF.kv_count | 33 |
| 4 | STRING | 1 | general.architecture | `qwen2` |
| 5 | STRING | 1 | general.type | `model` |
| 6 | STRING | 1 | general.name | `Hammer2.1 7b GGUF` |
| 7 | STRING | 1 | general.finetune | `GGUF` |
| 8 | STRING | 1 | general.basename | `Hammer2.1` |
| 9 | STRING | 1 | general.size_label | `7B` |
| 10 | UINT32 | 1 | qwen2.block_count | 28 |
| 11 | UINT32 | 1 | qwen2.context_length | 32768 |
| 12 | UINT32 | 1 | qwen2.embedding_length | 3584 |
| 13 | UINT32 | 1 | qwen2.feed_forward_length | 18944 |
| 14 | UINT32 | 1 | qwen2.attention.head_count | 28 |
| 15 | UINT32 | 1 | qwen2.attention.head_count_kv | 4 |
| 16 | FLOAT32 | 1 | qwen2.rope.freq_base | 1000000.0 |
| 17 | FLOAT32 | 1 | qwen2.attention.layer_norm_rms_epsilon | 1e-06 |
| 18 | STRING | 1 | qwen2.rope.scaling.type | `yarn` |
| 19 | FLOAT32 | 1 | qwen2.rope.scaling.factor | 4.0 |
| 20 | UINT32 | 1 | qwen2.rope.scaling.original_context_length | 32768 |
| 21 | STRING | 1 | tokenizer.ggml.model | `gpt2` |
| 22 | STRING | 1 | tokenizer.ggml.pre | `qwen2` |
| 23 | [STRING] | 151665 | tokenizer.ggml.tokens | [ `!`, `"`, `#`, `$`, `%`, ... ] |
| 24 | [INT32] | 151665 | tokenizer.ggml.token_type | [ 1, 1, 1, 1, 1, 1, 1, ... ] |
| 25 | [STRING] | 151387 | tokenizer.ggml.merges | [ `Ġ Ġ`, `ĠĠ ĠĠ`, `i n`, `Ġ t`, `ĠĠĠĠ ĠĠĠĠ`, ... ] |
| 26 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 151645 |
| 27 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 151643 |
| 28 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 151643 |
| 29 | BOOL | 1 | tokenizer.ggml.add_bos_token | False |
| 30 | STRING | 1 | tokenizer.chat_template | `{%- set system_message = 'You `...`{- '<|im_start|>assistant' }}` |
| 31 | UINT32 | 1 | general.quantization_version | 2 |
| 32 | UINT32 | 1 | general.file_type | 16 |
| 33 | STRING | 1 | quantize.imatrix.file | `./imatrix/imatrix-Hammer2.1-7b-small.dat` |
| 34 | STRING | 1 | quantize.imatrix.dataset | `../../datasets/imatrix/calibration_eur_small.txt` |
| 35 | INT32 | 1 | quantize.imatrix.entries_count | 197 |
| 36 | INT32 | 1 | quantize.imatrix.chunks_count | 968 |
## Tensors Overview ~8B Elements
Total number of elements in all tensors: 7612756480 Elements
- [Hammer2.1-7b-Q5\_K\_S.gguf - GGUF Internal File Dump](#hammer21-7b-q5_k_sgguf---gguf-internal-file-dump)
- [Key Value Metadata Store](#key-value-metadata-store)
- [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
- [Tensor Data Offset](#tensor-data-offset)
- [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
- [Block 0 Tensor Group : ~233M Elements](#block-0-tensor-group--233m-elements)
- [Block 1 Tensor Group : ~233M Elements](#block-1-tensor-group--233m-elements)
- [Block 2 Tensor Group : ~233M Elements](#block-2-tensor-group--233m-elements)
- [Block 3 Tensor Group : ~233M Elements](#block-3-tensor-group--233m-elements)
- [Block 4 Tensor Group : ~233M Elements](#block-4-tensor-group--233m-elements)
- [Block 5 Tensor Group : ~233M Elements](#block-5-tensor-group--233m-elements)
- [Block 6 Tensor Group : ~233M Elements](#block-6-tensor-group--233m-elements)
- [Block 7 Tensor Group : ~233M Elements](#block-7-tensor-group--233m-elements)
- [Block 8 Tensor Group : ~233M Elements](#block-8-tensor-group--233m-elements)
- [Block 9 Tensor Group : ~233M Elements](#block-9-tensor-group--233m-elements)
- [Block 10 Tensor Group : ~233M Elements](#block-10-tensor-group--233m-elements)
- [Block 11 Tensor Group : ~233M Elements](#block-11-tensor-group--233m-elements)
- [Block 12 Tensor Group : ~233M Elements](#block-12-tensor-group--233m-elements)
- [Block 13 Tensor Group : ~233M Elements](#block-13-tensor-group--233m-elements)
- [Block 14 Tensor Group : ~233M Elements](#block-14-tensor-group--233m-elements)
- [Block 15 Tensor Group : ~233M Elements](#block-15-tensor-group--233m-elements)
- [Block 16 Tensor Group : ~233M Elements](#block-16-tensor-group--233m-elements)
- [Block 17 Tensor Group : ~233M Elements](#block-17-tensor-group--233m-elements)
- [Block 18 Tensor Group : ~233M Elements](#block-18-tensor-group--233m-elements)
- [Block 19 Tensor Group : ~233M Elements](#block-19-tensor-group--233m-elements)
- [Block 20 Tensor Group : ~233M Elements](#block-20-tensor-group--233m-elements)
- [Block 21 Tensor Group : ~233M Elements](#block-21-tensor-group--233m-elements)
- [Block 22 Tensor Group : ~233M Elements](#block-22-tensor-group--233m-elements)
- [Block 23 Tensor Group : ~233M Elements](#block-23-tensor-group--233m-elements)
- [Block 24 Tensor Group : ~233M Elements](#block-24-tensor-group--233m-elements)
- [Block 25 Tensor Group : ~233M Elements](#block-25-tensor-group--233m-elements)
- [Block 26 Tensor Group : ~233M Elements](#block-26-tensor-group--233m-elements)
- [Block 27 Tensor Group : ~233M Elements](#block-27-tensor-group--233m-elements)
### Tensor Data Offset
This table contains the offset and data segment relative to start of file
| T_ID | Tensor Layer Name | Data Offset (B) | Data Size (B) |
|-----:|:--------------------------|-----------------:|-----------------:|
| 0 | output.weight | 0x5ab4c0 | 0x16463fa0 |
| 1 | output_norm.weight | 0x16a0f460 | 0x3800 |
| 2 | token_embd.weight | 0x16a12c60 | 0xdebe7c4 |
| 3 | blk.0.attn_k.bias | 0x248d1440 | 0x800 |
| 4 | blk.0.attn_k.weight | 0x248d1c40 | 0xfc000 |
| 5 | blk.0.attn_norm.weight | 0x249cdc40 | 0x3800 |
| 6 | blk.0.attn_output.weight | 0x249d1440 | 0x86c000 |
| 7 | blk.0.attn_q.bias | 0x2523d440 | 0x3800 |
| 8 | blk.0.attn_q.weight | 0x25240c40 | 0x6e4000 |
| 9 | blk.0.attn_v.bias | 0x25924c40 | 0x800 |
| 10 | blk.0.attn_v.weight | 0x25925440 | 0x134000 |
| 11 | blk.0.ffn_down.weight | 0x25a59440 | 0x2c84000 |
| 12 | blk.0.ffn_gate.weight | 0x286dd440 | 0x246c000 |
| 13 | blk.0.ffn_norm.weight | 0x2ab49440 | 0x3800 |
| 14 | blk.0.ffn_up.weight | 0x2ab4cc40 | 0x246c000 |
| 15 | blk.1.attn_k.bias | 0x2cfb8c40 | 0x800 |
| 16 | blk.1.attn_k.weight | 0x2cfb9440 | 0xfc000 |
| 17 | blk.1.attn_norm.weight | 0x2d0b5440 | 0x3800 |
| 18 | blk.1.attn_output.weight | 0x2d0b8c40 | 0x86c000 |
| 19 | blk.1.attn_q.bias | 0x2d924c40 | 0x3800 |
| 20 | blk.1.attn_q.weight | 0x2d928440 | 0x6e4000 |
| 21 | blk.1.attn_v.bias | 0x2e00c440 | 0x800 |
| 22 | blk.1.attn_v.weight | 0x2e00cc40 | 0x134000 |
| 23 | blk.1.ffn_down.weight | 0x2e140c40 | 0x2c84000 |
| 24 | blk.1.ffn_gate.weight | 0x30dc4c40 | 0x2c84000 |
| 25 | blk.1.ffn_norm.weight | 0x33a48c40 | 0x3800 |
| 26 | blk.1.ffn_up.weight | 0x33a4c440 | 0x2c84000 |
| 27 | blk.2.attn_k.bias | 0x366d0440 | 0x800 |
| 28 | blk.2.attn_k.weight | 0x366d0c40 | 0xfc000 |
| 29 | blk.2.attn_norm.weight | 0x367ccc40 | 0x3800 |
| 30 | blk.2.attn_output.weight | 0x367d0440 | 0x86c000 |
| 31 | blk.2.attn_q.bias | 0x3703c440 | 0x3800 |
| 32 | blk.2.attn_q.weight | 0x3703fc40 | 0x6e4000 |
| 33 | blk.2.attn_v.bias | 0x37723c40 | 0x800 |
| 34 | blk.2.attn_v.weight | 0x37724440 | 0x134000 |
| 35 | blk.2.ffn_down.weight | 0x37858440 | 0x2c84000 |
| 36 | blk.2.ffn_gate.weight | 0x3a4dc440 | 0x2c84000 |
| 37 | blk.2.ffn_norm.weight | 0x3d160440 | 0x3800 |
| 38 | blk.2.ffn_up.weight | 0x3d163c40 | 0x2c84000 |
| 39 | blk.3.attn_k.bias | 0x3fde7c40 | 0x800 |
| 40 | blk.3.attn_k.weight | 0x3fde8440 | 0xfc000 |
| 41 | blk.3.attn_norm.weight | 0x3fee4440 | 0x3800 |
| 42 | blk.3.attn_output.weight | 0x3fee7c40 | 0x86c000 |
| 43 | blk.3.attn_q.bias | 0x40753c40 | 0x3800 |
| 44 | blk.3.attn_q.weight | 0x40757440 | 0x6e4000 |
| 45 | blk.3.attn_v.bias | 0x40e3b440 | 0x800 |
| 46 | blk.3.attn_v.weight | 0x40e3bc40 | 0x134000 |
| 47 | blk.3.ffn_down.weight | 0x40f6fc40 | 0x351d800 |
| 48 | blk.3.ffn_gate.weight | 0x4448d440 | 0x2c84000 |
| 49 | blk.3.ffn_norm.weight | 0x47111440 | 0x3800 |
| 50 | blk.3.ffn_up.weight | 0x47114c40 | 0x2c84000 |
| 51 | blk.4.attn_k.bias | 0x49d98c40 | 0x800 |
| 52 | blk.4.attn_k.weight | 0x49d99440 | 0xfc000 |
| 53 | blk.4.attn_norm.weight | 0x49e95440 | 0x3800 |
| 54 | blk.4.attn_output.weight | 0x49e98c40 | 0x86c000 |
| 55 | blk.4.attn_q.bias | 0x4a704c40 | 0x3800 |
| 56 | blk.4.attn_q.weight | 0x4a708440 | 0x6e4000 |
| 57 | blk.4.attn_v.bias | 0x4adec440 | 0x800 |
| 58 | blk.4.attn_v.weight | 0x4adecc40 | 0x134000 |
| 59 | blk.4.ffn_down.weight | 0x4af20c40 | 0x2c84000 |
| 60 | blk.4.ffn_gate.weight | 0x4dba4c40 | 0x2c84000 |
| 61 | blk.4.ffn_norm.weight | 0x50828c40 | 0x3800 |
| 62 | blk.4.ffn_up.weight | 0x5082c440 | 0x2c84000 |
| 63 | blk.5.attn_k.bias | 0x534b0440 | 0x800 |
| 64 | blk.5.attn_k.weight | 0x534b0c40 | 0xfc000 |
| 65 | blk.5.attn_norm.weight | 0x535acc40 | 0x3800 |
| 66 | blk.5.attn_output.weight | 0x535b0440 | 0x86c000 |
| 67 | blk.5.attn_q.bias | 0x53e1c440 | 0x3800 |
| 68 | blk.5.attn_q.weight | 0x53e1fc40 | 0x6e4000 |
| 69 | blk.5.attn_v.bias | 0x54503c40 | 0x800 |
| 70 | blk.5.attn_v.weight | 0x54504440 | 0x134000 |
| 71 | blk.5.ffn_down.weight | 0x54638440 | 0x2c84000 |
| 72 | blk.5.ffn_gate.weight | 0x572bc440 | 0x2c84000 |
| 73 | blk.5.ffn_norm.weight | 0x59f40440 | 0x3800 |
| 74 | blk.5.ffn_up.weight | 0x59f43c40 | 0x2c84000 |
| 75 | blk.6.attn_k.bias | 0x5cbc7c40 | 0x800 |
| 76 | blk.6.attn_k.weight | 0x5cbc8440 | 0xfc000 |
| 77 | blk.6.attn_norm.weight | 0x5ccc4440 | 0x3800 |
| 78 | blk.6.attn_output.weight | 0x5ccc7c40 | 0x86c000 |
| 79 | blk.6.attn_q.bias | 0x5d533c40 | 0x3800 |
| 80 | blk.6.attn_q.weight | 0x5d537440 | 0x6e4000 |
| 81 | blk.6.attn_v.bias | 0x5dc1b440 | 0x800 |
| 82 | blk.6.attn_v.weight | 0x5dc1bc40 | 0x134000 |
| 83 | blk.6.ffn_down.weight | 0x5dd4fc40 | 0x2c84000 |
| 84 | blk.6.ffn_gate.weight | 0x609d3c40 | 0x246c000 |
| 85 | blk.6.ffn_norm.weight | 0x62e3fc40 | 0x3800 |
| 86 | blk.6.ffn_up.weight | 0x62e43440 | 0x246c000 |
| 87 | blk.7.attn_k.bias | 0x652af440 | 0x800 |
| 88 | blk.7.attn_k.weight | 0x652afc40 | 0xfc000 |
| 89 | blk.7.attn_norm.weight | 0x653abc40 | 0x3800 |
| 90 | blk.7.attn_output.weight | 0x653af440 | 0x86c000 |
| 91 | blk.7.attn_q.bias | 0x65c1b440 | 0x3800 |
| 92 | blk.7.attn_q.weight | 0x65c1ec40 | 0x6e4000 |
| 93 | blk.7.attn_v.bias | 0x66302c40 | 0x800 |
| 94 | blk.7.attn_v.weight | 0x66303440 | 0x134000 |
| 95 | blk.7.ffn_down.weight | 0x66437440 | 0x351d800 |
| 96 | blk.7.ffn_gate.weight | 0x69954c40 | 0x246c000 |
| 97 | blk.7.ffn_norm.weight | 0x6bdc0c40 | 0x3800 |
| 98 | blk.7.ffn_up.weight | 0x6bdc4440 | 0x246c000 |
| 99 | blk.8.attn_k.bias | 0x6e230440 | 0x800 |
| 100 | blk.8.attn_k.weight | 0x6e230c40 | 0xfc000 |
| 101 | blk.8.attn_norm.weight | 0x6e32cc40 | 0x3800 |
| 102 | blk.8.attn_output.weight | 0x6e330440 | 0x86c000 |
| 103 | blk.8.attn_q.bias | 0x6eb9c440 | 0x3800 |
| 104 | blk.8.attn_q.weight | 0x6eb9fc40 | 0x6e4000 |
| 105 | blk.8.attn_v.bias | 0x6f283c40 | 0x800 |
| 106 | blk.8.attn_v.weight | 0x6f284440 | 0x134000 |
| 107 | blk.8.ffn_down.weight | 0x6f3b8440 | 0x2c84000 |
| 108 | blk.8.ffn_gate.weight | 0x7203c440 | 0x246c000 |
| 109 | blk.8.ffn_norm.weight | 0x744a8440 | 0x3800 |
| 110 | blk.8.ffn_up.weight | 0x744abc40 | 0x246c000 |
| 111 | blk.9.attn_k.bias | 0x76917c40 | 0x800 |
| 112 | blk.9.attn_k.weight | 0x76918440 | 0xfc000 |
| 113 | blk.9.attn_norm.weight | 0x76a14440 | 0x3800 |
| 114 | blk.9.attn_output.weight | 0x76a17c40 | 0x86c000 |
| 115 | blk.9.attn_q.bias | 0x77283c40 | 0x3800 |
| 116 | blk.9.attn_q.weight | 0x77287440 | 0x6e4000 |
| 117 | blk.9.attn_v.bias | 0x7796b440 | 0x800 |
| 118 | blk.9.attn_v.weight | 0x7796bc40 | 0x134000 |
| 119 | blk.9.ffn_down.weight | 0x77a9fc40 | 0x351d800 |
| 120 | blk.9.ffn_gate.weight | 0x7afbd440 | 0x2c84000 |
| 121 | blk.9.ffn_norm.weight | 0x7dc41440 | 0x3800 |
| 122 | blk.9.ffn_up.weight | 0x7dc44c40 | 0x2c84000 |
| 123 | blk.10.attn_k.bias | 0x808c8c40 | 0x800 |
| 124 | blk.10.attn_k.weight | 0x808c9440 | 0xfc000 |
| 125 | blk.10.attn_norm.weight | 0x809c5440 | 0x3800 |
| 126 | blk.10.attn_output.weight | 0x809c8c40 | 0x86c000 |
| 127 | blk.10.attn_q.bias | 0x81234c40 | 0x3800 |
| 128 | blk.10.attn_q.weight | 0x81238440 | 0x6e4000 |
| 129 | blk.10.attn_v.bias | 0x8191c440 | 0x800 |
| 130 | blk.10.attn_v.weight | 0x8191cc40 | 0x134000 |
| 131 | blk.10.ffn_down.weight | 0x81a50c40 | 0x351d800 |
| 132 | blk.10.ffn_gate.weight | 0x84f6e440 | 0x246c000 |
| 133 | blk.10.ffn_norm.weight | 0x873da440 | 0x3800 |
| 134 | blk.10.ffn_up.weight | 0x873ddc40 | 0x246c000 |
| 135 | blk.11.attn_k.bias | 0x89849c40 | 0x800 |
| 136 | blk.11.attn_k.weight | 0x8984a440 | 0xfc000 |
| 137 | blk.11.attn_norm.weight | 0x89946440 | 0x3800 |
| 138 | blk.11.attn_output.weight | 0x89949c40 | 0x86c000 |
| 139 | blk.11.attn_q.bias | 0x8a1b5c40 | 0x3800 |
| 140 | blk.11.attn_q.weight | 0x8a1b9440 | 0x6e4000 |
| 141 | blk.11.attn_v.bias | 0x8a89d440 | 0x800 |
| 142 | blk.11.attn_v.weight | 0x8a89dc40 | 0x134000 |
| 143 | blk.11.ffn_down.weight | 0x8a9d1c40 | 0x2c84000 |
| 144 | blk.11.ffn_gate.weight | 0x8d655c40 | 0x246c000 |
| 145 | blk.11.ffn_norm.weight | 0x8fac1c40 | 0x3800 |
| 146 | blk.11.ffn_up.weight | 0x8fac5440 | 0x246c000 |
| 147 | blk.12.attn_k.bias | 0x91f31440 | 0x800 |
| 148 | blk.12.attn_k.weight | 0x91f31c40 | 0xfc000 |
| 149 | blk.12.attn_norm.weight | 0x9202dc40 | 0x3800 |
| 150 | blk.12.attn_output.weight | 0x92031440 | 0x86c000 |
| 151 | blk.12.attn_q.bias | 0x9289d440 | 0x3800 |
| 152 | blk.12.attn_q.weight | 0x928a0c40 | 0x6e4000 |
| 153 | blk.12.attn_v.bias | 0x92f84c40 | 0x800 |
| 154 | blk.12.attn_v.weight | 0x92f85440 | 0x134000 |
| 155 | blk.12.ffn_down.weight | 0x930b9440 | 0x2c84000 |
| 156 | blk.12.ffn_gate.weight | 0x95d3d440 | 0x246c000 |
| 157 | blk.12.ffn_norm.weight | 0x981a9440 | 0x3800 |
| 158 | blk.12.ffn_up.weight | 0x981acc40 | 0x246c000 |
| 159 | blk.13.attn_k.bias | 0x9a618c40 | 0x800 |
| 160 | blk.13.attn_k.weight | 0x9a619440 | 0xfc000 |
| 161 | blk.13.attn_norm.weight | 0x9a715440 | 0x3800 |
| 162 | blk.13.attn_output.weight | 0x9a718c40 | 0x86c000 |
| 163 | blk.13.attn_q.bias | 0x9af84c40 | 0x3800 |
| 164 | blk.13.attn_q.weight | 0x9af88440 | 0x6e4000 |
| 165 | blk.13.attn_v.bias | 0x9b66c440 | 0x800 |
| 166 | blk.13.attn_v.weight | 0x9b66cc40 | 0x134000 |
| 167 | blk.13.ffn_down.weight | 0x9b7a0c40 | 0x2c84000 |
| 168 | blk.13.ffn_gate.weight | 0x9e424c40 | 0x246c000 |
| 169 | blk.13.ffn_norm.weight | 0xa0890c40 | 0x3800 |
| 170 | blk.13.ffn_up.weight | 0xa0894440 | 0x246c000 |
| 171 | blk.14.attn_k.bias | 0xa2d00440 | 0x800 |
| 172 | blk.14.attn_k.weight | 0xa2d00c40 | 0x134000 |
| 173 | blk.14.attn_norm.weight | 0xa2e34c40 | 0x3800 |
| 174 | blk.14.attn_output.weight | 0xa2e38440 | 0x86c000 |
| 175 | blk.14.attn_q.bias | 0xa36a4440 | 0x3800 |
| 176 | blk.14.attn_q.weight | 0xa36a7c40 | 0x86c000 |
| 177 | blk.14.attn_v.bias | 0xa3f13c40 | 0x800 |
| 178 | blk.14.attn_v.weight | 0xa3f14440 | 0x134000 |
| 179 | blk.14.ffn_down.weight | 0xa4048440 | 0x2c84000 |
| 180 | blk.14.ffn_gate.weight | 0xa6ccc440 | 0x246c000 |
| 181 | blk.14.ffn_norm.weight | 0xa9138440 | 0x3800 |
| 182 | blk.14.ffn_up.weight | 0xa913bc40 | 0x246c000 |
| 183 | blk.15.attn_k.bias | 0xab5a7c40 | 0x800 |
| 184 | blk.15.attn_k.weight | 0xab5a8440 | 0x134000 |
| 185 | blk.15.attn_norm.weight | 0xab6dc440 | 0x3800 |
| 186 | blk.15.attn_output.weight | 0xab6dfc40 | 0x86c000 |
| 187 | blk.15.attn_q.bias | 0xabf4bc40 | 0x3800 |
| 188 | blk.15.attn_q.weight | 0xabf4f440 | 0x86c000 |
| 189 | blk.15.attn_v.bias | 0xac7bb440 | 0x800 |
| 190 | blk.15.attn_v.weight | 0xac7bbc40 | 0x134000 |
| 191 | blk.15.ffn_down.weight | 0xac8efc40 | 0x2c84000 |
| 192 | blk.15.ffn_gate.weight | 0xaf573c40 | 0x246c000 |
| 193 | blk.15.ffn_norm.weight | 0xb19dfc40 | 0x3800 |
| 194 | blk.15.ffn_up.weight | 0xb19e3440 | 0x246c000 |
| 195 | blk.16.attn_k.bias | 0xb3e4f440 | 0x800 |
| 196 | blk.16.attn_k.weight | 0xb3e4fc40 | 0x134000 |
| 197 | blk.16.attn_norm.weight | 0xb3f83c40 | 0x3800 |
| 198 | blk.16.attn_output.weight | 0xb3f87440 | 0x86c000 |
| 199 | blk.16.attn_q.bias | 0xb47f3440 | 0x3800 |
| 200 | blk.16.attn_q.weight | 0xb47f6c40 | 0x86c000 |
| 201 | blk.16.attn_v.bias | 0xb5062c40 | 0x800 |
| 202 | blk.16.attn_v.weight | 0xb5063440 | 0x134000 |
| 203 | blk.16.ffn_down.weight | 0xb5197440 | 0x2c84000 |
| 204 | blk.16.ffn_gate.weight | 0xb7e1b440 | 0x246c000 |
| 205 | blk.16.ffn_norm.weight | 0xba287440 | 0x3800 |
| 206 | blk.16.ffn_up.weight | 0xba28ac40 | 0x246c000 |
| 207 | blk.17.attn_k.bias | 0xbc6f6c40 | 0x800 |
| 208 | blk.17.attn_k.weight | 0xbc6f7440 | 0x134000 |
| 209 | blk.17.attn_norm.weight | 0xbc82b440 | 0x3800 |
| 210 | blk.17.attn_output.weight | 0xbc82ec40 | 0x86c000 |
| 211 | blk.17.attn_q.bias | 0xbd09ac40 | 0x3800 |
| 212 | blk.17.attn_q.weight | 0xbd09e440 | 0x86c000 |
| 213 | blk.17.attn_v.bias | 0xbd90a440 | 0x800 |
| 214 | blk.17.attn_v.weight | 0xbd90ac40 | 0x134000 |
| 215 | blk.17.ffn_down.weight | 0xbda3ec40 | 0x2c84000 |
| 216 | blk.17.ffn_gate.weight | 0xc06c2c40 | 0x246c000 |
| 217 | blk.17.ffn_norm.weight | 0xc2b2ec40 | 0x3800 |
| 218 | blk.17.ffn_up.weight | 0xc2b32440 | 0x246c000 |
| 219 | blk.18.attn_k.bias | 0xc4f9e440 | 0x800 |
| 220 | blk.18.attn_k.weight | 0xc4f9ec40 | 0x134000 |
| 221 | blk.18.attn_norm.weight | 0xc50d2c40 | 0x3800 |
| 222 | blk.18.attn_output.weight | 0xc50d6440 | 0x86c000 |
| 223 | blk.18.attn_q.bias | 0xc5942440 | 0x3800 |
| 224 | blk.18.attn_q.weight | 0xc5945c40 | 0x86c000 |
| 225 | blk.18.attn_v.bias | 0xc61b1c40 | 0x800 |
| 226 | blk.18.attn_v.weight | 0xc61b2440 | 0x134000 |
| 227 | blk.18.ffn_down.weight | 0xc62e6440 | 0x351d800 |
| 228 | blk.18.ffn_gate.weight | 0xc9803c40 | 0x246c000 |
| 229 | blk.18.ffn_norm.weight | 0xcbc6fc40 | 0x3800 |
| 230 | blk.18.ffn_up.weight | 0xcbc73440 | 0x246c000 |
| 231 | blk.19.attn_k.bias | 0xce0df440 | 0x800 |
| 232 | blk.19.attn_k.weight | 0xce0dfc40 | 0x134000 |
| 233 | blk.19.attn_norm.weight | 0xce213c40 | 0x3800 |
| 234 | blk.19.attn_output.weight | 0xce217440 | 0x86c000 |
| 235 | blk.19.attn_q.bias | 0xcea83440 | 0x3800 |
| 236 | blk.19.attn_q.weight | 0xcea86c40 | 0x86c000 |
| 237 | blk.19.attn_v.bias | 0xcf2f2c40 | 0x800 |
| 238 | blk.19.attn_v.weight | 0xcf2f3440 | 0x134000 |
| 239 | blk.19.ffn_down.weight | 0xcf427440 | 0x351d800 |
| 240 | blk.19.ffn_gate.weight | 0xd2944c40 | 0x246c000 |
| 241 | blk.19.ffn_norm.weight | 0xd4db0c40 | 0x3800 |
| 242 | blk.19.ffn_up.weight | 0xd4db4440 | 0x246c000 |
| 243 | blk.20.attn_k.bias | 0xd7220440 | 0x800 |
| 244 | blk.20.attn_k.weight | 0xd7220c40 | 0x134000 |
| 245 | blk.20.attn_norm.weight | 0xd7354c40 | 0x3800 |
| 246 | blk.20.attn_output.weight | 0xd7358440 | 0x86c000 |
| 247 | blk.20.attn_q.bias | 0xd7bc4440 | 0x3800 |
| 248 | blk.20.attn_q.weight | 0xd7bc7c40 | 0x86c000 |
| 249 | blk.20.attn_v.bias | 0xd8433c40 | 0x800 |
| 250 | blk.20.attn_v.weight | 0xd8434440 | 0x134000 |
| 251 | blk.20.ffn_down.weight | 0xd8568440 | 0x351d800 |
| 252 | blk.20.ffn_gate.weight | 0xdba85c40 | 0x2c84000 |
| 253 | blk.20.ffn_norm.weight | 0xde709c40 | 0x3800 |
| 254 | blk.20.ffn_up.weight | 0xde70d440 | 0x2c84000 |
| 255 | blk.21.attn_k.bias | 0xe1391440 | 0x800 |
| 256 | blk.21.attn_k.weight | 0xe1391c40 | 0x134000 |
| 257 | blk.21.attn_norm.weight | 0xe14c5c40 | 0x3800 |
| 258 | blk.21.attn_output.weight | 0xe14c9440 | 0x86c000 |
| 259 | blk.21.attn_q.bias | 0xe1d35440 | 0x3800 |
| 260 | blk.21.attn_q.weight | 0xe1d38c40 | 0x86c000 |
| 261 | blk.21.attn_v.bias | 0xe25a4c40 | 0x800 |
| 262 | blk.21.attn_v.weight | 0xe25a5440 | 0x134000 |
| 263 | blk.21.ffn_down.weight | 0xe26d9440 | 0x351d800 |
| 264 | blk.21.ffn_gate.weight | 0xe5bf6c40 | 0x2c84000 |
| 265 | blk.21.ffn_norm.weight | 0xe887ac40 | 0x3800 |
| 266 | blk.21.ffn_up.weight | 0xe887e440 | 0x2c84000 |
| 267 | blk.22.attn_k.bias | 0xeb502440 | 0x800 |
| 268 | blk.22.attn_k.weight | 0xeb502c40 | 0x134000 |
| 269 | blk.22.attn_norm.weight | 0xeb636c40 | 0x3800 |
| 270 | blk.22.attn_output.weight | 0xeb63a440 | 0x86c000 |
| 271 | blk.22.attn_q.bias | 0xebea6440 | 0x3800 |
| 272 | blk.22.attn_q.weight | 0xebea9c40 | 0x86c000 |
| 273 | blk.22.attn_v.bias | 0xec715c40 | 0x800 |
| 274 | blk.22.attn_v.weight | 0xec716440 | 0x134000 |
| 275 | blk.22.ffn_down.weight | 0xec84a440 | 0x351d800 |
| 276 | blk.22.ffn_gate.weight | 0xefd67c40 | 0x2c84000 |
| 277 | blk.22.ffn_norm.weight | 0xf29ebc40 | 0x3800 |
| 278 | blk.22.ffn_up.weight | 0xf29ef440 | 0x2c84000 |
| 279 | blk.23.attn_k.bias | 0xf5673440 | 0x800 |
| 280 | blk.23.attn_k.weight | 0xf5673c40 | 0x134000 |
| 281 | blk.23.attn_norm.weight | 0xf57a7c40 | 0x3800 |
| 282 | blk.23.attn_output.weight | 0xf57ab440 | 0x86c000 |
| 283 | blk.23.attn_q.bias | 0xf6017440 | 0x3800 |
| 284 | blk.23.attn_q.weight | 0xf601ac40 | 0x86c000 |
| 285 | blk.23.attn_v.bias | 0xf6886c40 | 0x800 |
| 286 | blk.23.attn_v.weight | 0xf6887440 | 0x134000 |
| 287 | blk.23.ffn_down.weight | 0xf69bb440 | 0x351d800 |
| 288 | blk.23.ffn_gate.weight | 0xf9ed8c40 | 0x2c84000 |
| 289 | blk.23.ffn_norm.weight | 0xfcb5cc40 | 0x3800 |
| 290 | blk.23.ffn_up.weight | 0xfcb60440 | 0x2c84000 |
| 291 | blk.24.attn_k.bias | 0xff7e4440 | 0x800 |
| 292 | blk.24.attn_k.weight | 0xff7e4c40 | 0x134000 |
| 293 | blk.24.attn_norm.weight | 0xff918c40 | 0x3800 |
| 294 | blk.24.attn_output.weight | 0xff91c440 | 0x86c000 |
| 295 | blk.24.attn_q.bias | 0x100188440 | 0x3800 |
| 296 | blk.24.attn_q.weight | 0x10018bc40 | 0x86c000 |
| 297 | blk.24.attn_v.bias | 0x1009f7c40 | 0x800 |
| 298 | blk.24.attn_v.weight | 0x1009f8440 | 0x134000 |
| 299 | blk.24.ffn_down.weight | 0x100b2c440 | 0x351d800 |
| 300 | blk.24.ffn_gate.weight | 0x104049c40 | 0x2c84000 |
| 301 | blk.24.ffn_norm.weight | 0x106ccdc40 | 0x3800 |
| 302 | blk.24.ffn_up.weight | 0x106cd1440 | 0x2c84000 |
| 303 | blk.25.attn_k.bias | 0x109955440 | 0x800 |
| 304 | blk.25.attn_k.weight | 0x109955c40 | 0x134000 |
| 305 | blk.25.attn_norm.weight | 0x109a89c40 | 0x3800 |
| 306 | blk.25.attn_output.weight | 0x109a8d440 | 0x86c000 |
| 307 | blk.25.attn_q.bias | 0x10a2f9440 | 0x3800 |
| 308 | blk.25.attn_q.weight | 0x10a2fcc40 | 0x86c000 |
| 309 | blk.25.attn_v.bias | 0x10ab68c40 | 0x800 |
| 310 | blk.25.attn_v.weight | 0x10ab69440 | 0x134000 |
| 311 | blk.25.ffn_down.weight | 0x10ac9d440 | 0x351d800 |
| 312 | blk.25.ffn_gate.weight | 0x10e1bac40 | 0x2c84000 |
| 313 | blk.25.ffn_norm.weight | 0x110e3ec40 | 0x3800 |
| 314 | blk.25.ffn_up.weight | 0x110e42440 | 0x2c84000 |
| 315 | blk.26.attn_k.bias | 0x113ac6440 | 0x800 |
| 316 | blk.26.attn_k.weight | 0x113ac6c40 | 0x134000 |
| 317 | blk.26.attn_norm.weight | 0x113bfac40 | 0x3800 |
| 318 | blk.26.attn_output.weight | 0x113bfe440 | 0x86c000 |
| 319 | blk.26.attn_q.bias | 0x11446a440 | 0x3800 |
| 320 | blk.26.attn_q.weight | 0x11446dc40 | 0x86c000 |
| 321 | blk.26.attn_v.bias | 0x114cd9c40 | 0x800 |
| 322 | blk.26.attn_v.weight | 0x114cda440 | 0x134000 |
| 323 | blk.26.ffn_down.weight | 0x114e0e440 | 0x351d800 |
| 324 | blk.26.ffn_gate.weight | 0x11832bc40 | 0x2c84000 |
| 325 | blk.26.ffn_norm.weight | 0x11afafc40 | 0x3800 |
| 326 | blk.26.ffn_up.weight | 0x11afb3440 | 0x2c84000 |
| 327 | blk.27.attn_k.bias | 0x11dc37440 | 0x800 |
| 328 | blk.27.attn_k.weight | 0x11dc37c40 | 0x134000 |
| 329 | blk.27.attn_norm.weight | 0x11dd6bc40 | 0x3800 |
| 330 | blk.27.attn_output.weight | 0x11dd6f440 | 0x86c000 |
| 331 | blk.27.attn_q.bias | 0x11e5db440 | 0x3800 |
| 332 | blk.27.attn_q.weight | 0x11e5dec40 | 0x86c000 |
| 333 | blk.27.attn_v.bias | 0x11ee4ac40 | 0x800 |
| 334 | blk.27.attn_v.weight | 0x11ee4b440 | 0x134000 |
| 335 | blk.27.ffn_down.weight | 0x11ef7f440 | 0x351d800 |
| 336 | blk.27.ffn_gate.weight | 0x12249cc40 | 0x2c84000 |
| 337 | blk.27.ffn_norm.weight | 0x125120c40 | 0x3800 |
| 338 | blk.27.ffn_up.weight | 0x125124440 | 0x2c84000 |
### Base Tensor Group : ~1B Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
| 0 | output.weight | Output (W) | (~544M) 543567360 | 3584 x 151665 x 1 x 1 | Q5_K |
| 1 | output_norm.weight | Output Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 2 | token_embd.weight | Token Embedding (W) | (~544M) 543567360 | 3584 x 151665 x 1 x 1 | Q3_K |
- Total elements in base: ( ~1B) 1087138304
- Percentage of total elements: 14.28%
### Block 0 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 3 | blk.0.attn_k.bias | Block 0 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 4 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 5 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 6 | blk.0.attn_output.weight | Block 0 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 7 | blk.0.attn_q.bias | Block 0 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 8 | blk.0.attn_q.weight | Block 0 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 9 | blk.0.attn_v.bias | Block 0 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 10 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 11 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 12 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 13 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 14 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.0: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 1 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 15 | blk.1.attn_k.bias | Block 1 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 16 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 17 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 18 | blk.1.attn_output.weight | Block 1 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 19 | blk.1.attn_q.bias | Block 1 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 20 | blk.1.attn_q.weight | Block 1 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 21 | blk.1.attn_v.bias | Block 1 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 22 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 23 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 24 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 25 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 26 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.1: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 2 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 27 | blk.2.attn_k.bias | Block 2 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 28 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 29 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 30 | blk.2.attn_output.weight | Block 2 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 31 | blk.2.attn_q.bias | Block 2 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 32 | blk.2.attn_q.weight | Block 2 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 33 | blk.2.attn_v.bias | Block 2 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 34 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 35 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 36 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 37 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 38 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.2: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 3 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 39 | blk.3.attn_k.bias | Block 3 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 40 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 41 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 42 | blk.3.attn_output.weight | Block 3 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 43 | blk.3.attn_q.bias | Block 3 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 44 | blk.3.attn_q.weight | Block 3 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 45 | blk.3.attn_v.bias | Block 3 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 46 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 47 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 48 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 49 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 50 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.3: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 4 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 51 | blk.4.attn_k.bias | Block 4 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 52 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 53 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 54 | blk.4.attn_output.weight | Block 4 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 55 | blk.4.attn_q.bias | Block 4 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 56 | blk.4.attn_q.weight | Block 4 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 57 | blk.4.attn_v.bias | Block 4 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 58 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 59 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 60 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 61 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 62 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.4: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 5 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 63 | blk.5.attn_k.bias | Block 5 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 64 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 65 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 66 | blk.5.attn_output.weight | Block 5 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 67 | blk.5.attn_q.bias | Block 5 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 68 | blk.5.attn_q.weight | Block 5 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 69 | blk.5.attn_v.bias | Block 5 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 70 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 71 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 72 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 73 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 74 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.5: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 6 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 75 | blk.6.attn_k.bias | Block 6 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 76 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 77 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 78 | blk.6.attn_output.weight | Block 6 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 79 | blk.6.attn_q.bias | Block 6 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 80 | blk.6.attn_q.weight | Block 6 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 81 | blk.6.attn_v.bias | Block 6 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 82 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 83 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 84 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 85 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 86 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.6: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 7 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 87 | blk.7.attn_k.bias | Block 7 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 88 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 89 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 90 | blk.7.attn_output.weight | Block 7 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 91 | blk.7.attn_q.bias | Block 7 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 92 | blk.7.attn_q.weight | Block 7 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 93 | blk.7.attn_v.bias | Block 7 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 94 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 95 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 96 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 97 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 98 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.7: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 8 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 99 | blk.8.attn_k.bias | Block 8 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 100 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 101 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 102 | blk.8.attn_output.weight | Block 8 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 103 | blk.8.attn_q.bias | Block 8 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 104 | blk.8.attn_q.weight | Block 8 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 105 | blk.8.attn_v.bias | Block 8 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 106 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 107 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 108 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 109 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 110 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.8: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 9 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 111 | blk.9.attn_k.bias | Block 9 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 112 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 113 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 114 | blk.9.attn_output.weight | Block 9 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 115 | blk.9.attn_q.bias | Block 9 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 116 | blk.9.attn_q.weight | Block 9 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 117 | blk.9.attn_v.bias | Block 9 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 118 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 119 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 120 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 121 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 122 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.9: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 10 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 123 | blk.10.attn_k.bias | Block 10 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 124 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 125 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 126 | blk.10.attn_output.weight | Block 10 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 127 | blk.10.attn_q.bias | Block 10 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 128 | blk.10.attn_q.weight | Block 10 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 129 | blk.10.attn_v.bias | Block 10 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 130 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 131 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 132 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 133 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 134 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.10: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 11 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 135 | blk.11.attn_k.bias | Block 11 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 136 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 137 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 138 | blk.11.attn_output.weight | Block 11 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 139 | blk.11.attn_q.bias | Block 11 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 140 | blk.11.attn_q.weight | Block 11 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 141 | blk.11.attn_v.bias | Block 11 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 142 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 143 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 144 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 145 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 146 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.11: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 12 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 147 | blk.12.attn_k.bias | Block 12 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 148 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 149 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 150 | blk.12.attn_output.weight | Block 12 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 151 | blk.12.attn_q.bias | Block 12 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 152 | blk.12.attn_q.weight | Block 12 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 153 | blk.12.attn_v.bias | Block 12 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 154 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 155 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 156 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 157 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 158 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.12: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 13 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 159 | blk.13.attn_k.bias | Block 13 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 160 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q4_K |
| 161 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 162 | blk.13.attn_output.weight | Block 13 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 163 | blk.13.attn_q.bias | Block 13 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 164 | blk.13.attn_q.weight | Block 13 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q4_K |
| 165 | blk.13.attn_v.bias | Block 13 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 166 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 167 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 168 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 169 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 170 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.13: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 14 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 171 | blk.14.attn_k.bias | Block 14 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 172 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 173 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 174 | blk.14.attn_output.weight | Block 14 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 175 | blk.14.attn_q.bias | Block 14 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 176 | blk.14.attn_q.weight | Block 14 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 177 | blk.14.attn_v.bias | Block 14 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 178 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 179 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 180 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 181 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 182 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.14: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 15 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 183 | blk.15.attn_k.bias | Block 15 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 184 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 185 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 186 | blk.15.attn_output.weight | Block 15 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 187 | blk.15.attn_q.bias | Block 15 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 188 | blk.15.attn_q.weight | Block 15 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 189 | blk.15.attn_v.bias | Block 15 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 190 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 191 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 192 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 193 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 194 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.15: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 16 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 195 | blk.16.attn_k.bias | Block 16 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 196 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 197 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 198 | blk.16.attn_output.weight | Block 16 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 199 | blk.16.attn_q.bias | Block 16 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 200 | blk.16.attn_q.weight | Block 16 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 201 | blk.16.attn_v.bias | Block 16 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 202 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 203 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 204 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 205 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 206 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.16: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 17 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 207 | blk.17.attn_k.bias | Block 17 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 208 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 209 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 210 | blk.17.attn_output.weight | Block 17 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 211 | blk.17.attn_q.bias | Block 17 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 212 | blk.17.attn_q.weight | Block 17 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 213 | blk.17.attn_v.bias | Block 17 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 214 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 215 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q5_K |
| 216 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 217 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 218 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.17: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 18 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 219 | blk.18.attn_k.bias | Block 18 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 220 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 221 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 222 | blk.18.attn_output.weight | Block 18 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 223 | blk.18.attn_q.bias | Block 18 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 224 | blk.18.attn_q.weight | Block 18 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 225 | blk.18.attn_v.bias | Block 18 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 226 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 227 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 228 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 229 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 230 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.18: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 19 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 231 | blk.19.attn_k.bias | Block 19 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 232 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 233 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 234 | blk.19.attn_output.weight | Block 19 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 235 | blk.19.attn_q.bias | Block 19 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 236 | blk.19.attn_q.weight | Block 19 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 237 | blk.19.attn_v.bias | Block 19 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 238 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 239 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 240 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
| 241 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 242 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q4_K |
- Total elements in blk.19: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 20 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 243 | blk.20.attn_k.bias | Block 20 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 244 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 245 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 246 | blk.20.attn_output.weight | Block 20 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 247 | blk.20.attn_q.bias | Block 20 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 248 | blk.20.attn_q.weight | Block 20 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 249 | blk.20.attn_v.bias | Block 20 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 250 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 251 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 252 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 253 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 254 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.20: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 21 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 255 | blk.21.attn_k.bias | Block 21 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 256 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 257 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 258 | blk.21.attn_output.weight | Block 21 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 259 | blk.21.attn_q.bias | Block 21 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 260 | blk.21.attn_q.weight | Block 21 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 261 | blk.21.attn_v.bias | Block 21 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 262 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 263 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 264 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 265 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 266 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.21: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 22 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 267 | blk.22.attn_k.bias | Block 22 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 268 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 269 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 270 | blk.22.attn_output.weight | Block 22 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 271 | blk.22.attn_q.bias | Block 22 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 272 | blk.22.attn_q.weight | Block 22 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 273 | blk.22.attn_v.bias | Block 22 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 274 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 275 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 276 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 277 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 278 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.22: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 23 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 279 | blk.23.attn_k.bias | Block 23 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 280 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 281 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 282 | blk.23.attn_output.weight | Block 23 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 283 | blk.23.attn_q.bias | Block 23 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 284 | blk.23.attn_q.weight | Block 23 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 285 | blk.23.attn_v.bias | Block 23 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 286 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 287 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 288 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 289 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 290 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.23: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 24 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 291 | blk.24.attn_k.bias | Block 24 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 292 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 293 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 294 | blk.24.attn_output.weight | Block 24 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 295 | blk.24.attn_q.bias | Block 24 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 296 | blk.24.attn_q.weight | Block 24 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 297 | blk.24.attn_v.bias | Block 24 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 298 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 299 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 300 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 301 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 302 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.24: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 25 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 303 | blk.25.attn_k.bias | Block 25 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 304 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 305 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 306 | blk.25.attn_output.weight | Block 25 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 307 | blk.25.attn_q.bias | Block 25 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 308 | blk.25.attn_q.weight | Block 25 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 309 | blk.25.attn_v.bias | Block 25 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 310 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 311 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 312 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 313 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 314 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.25: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 26 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 315 | blk.26.attn_k.bias | Block 26 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 316 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 317 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 318 | blk.26.attn_output.weight | Block 26 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 319 | blk.26.attn_q.bias | Block 26 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 320 | blk.26.attn_q.weight | Block 26 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 321 | blk.26.attn_v.bias | Block 26 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 322 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 323 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 324 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 325 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 326 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.26: (~233M) 233057792
- Percentage of total elements: 3.06%
### Block 27 Tensor Group : ~233M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 327 | blk.27.attn_k.bias | Block 27 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 328 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 329 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 330 | blk.27.attn_output.weight | Block 27 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 331 | blk.27.attn_q.bias | Block 27 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 332 | blk.27.attn_q.weight | Block 27 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | Q5_K |
| 333 | blk.27.attn_v.bias | Block 27 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 334 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | Q5_K |
| 335 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | Q6_K |
| 336 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
| 337 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 338 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | Q5_K |
- Total elements in blk.27: (~233M) 233057792
- Percentage of total elements: 3.06%