# Hammer2.1-7b-F16.gguf - GGUF Internal File Dump
- Endian: LITTLE endian
## Key Value Metadata Store
There are 32 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 | 29 |
| 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 | UINT32 | 1 | general.file_type | 1 |
| 19 | STRING | 1 | qwen2.rope.scaling.type | `yarn` |
| 20 | FLOAT32 | 1 | qwen2.rope.scaling.factor | 4.0 |
| 21 | UINT32 | 1 | qwen2.rope.scaling.original_context_length | 32768 |
| 22 | STRING | 1 | tokenizer.ggml.model | `gpt2` |
| 23 | STRING | 1 | tokenizer.ggml.pre | `qwen2` |
| 24 | [STRING] | 151665 | tokenizer.ggml.tokens | [ `!`, `"`, `#`, `$`, `%`, ... ] |
| 25 | [INT32] | 151665 | tokenizer.ggml.token_type | [ 1, 1, 1, 1, 1, 1, 1, ... ] |
| 26 | [STRING] | 151387 | tokenizer.ggml.merges | [ `Ġ Ġ`, `ĠĠ ĠĠ`, `i n`, `Ġ t`, `ĠĠĠĠ ĠĠĠĠ`, ... ] |
| 27 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 151645 |
| 28 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 151643 |
| 29 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 151643 |
| 30 | BOOL | 1 | tokenizer.ggml.add_bos_token | False |
| 31 | STRING | 1 | tokenizer.chat_template | `{%- set system_message = 'You `...`{- '<|im_start|>assistant' }}` |
| 32 | UINT32 | 1 | general.quantization_version | 2 |
## Tensors Overview ~8B Elements
Total number of elements in all tensors: 7612756480 Elements
- [Hammer2.1-7b-F16.gguf - GGUF Internal File Dump](#hammer21-7b-f16gguf---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 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 9 Tensor Group : ~233M Elements](#block-9-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 | token_embd.weight | 0x5ab3a0 | 0x40cc5c00 |
| 1 | blk.0.attn_norm.weight | 0x41270fa0 | 0x3800 |
| 2 | blk.0.ffn_down.weight | 0x412747a0 | 0x8180000 |
| 3 | blk.0.ffn_gate.weight | 0x493f47a0 | 0x8180000 |
| 4 | blk.0.ffn_up.weight | 0x515747a0 | 0x8180000 |
| 5 | blk.0.ffn_norm.weight | 0x596f47a0 | 0x3800 |
| 6 | blk.0.attn_k.bias | 0x596f7fa0 | 0x800 |
| 7 | blk.0.attn_k.weight | 0x596f87a0 | 0x380000 |
| 8 | blk.0.attn_output.weight | 0x59a787a0 | 0x1880000 |
| 9 | blk.0.attn_q.bias | 0x5b2f87a0 | 0x3800 |
| 10 | blk.0.attn_q.weight | 0x5b2fbfa0 | 0x1880000 |
| 11 | blk.0.attn_v.bias | 0x5cb7bfa0 | 0x800 |
| 12 | blk.0.attn_v.weight | 0x5cb7c7a0 | 0x380000 |
| 13 | blk.1.attn_norm.weight | 0x5cefc7a0 | 0x3800 |
| 14 | blk.1.ffn_down.weight | 0x5cefffa0 | 0x8180000 |
| 15 | blk.1.ffn_gate.weight | 0x6507ffa0 | 0x8180000 |
| 16 | blk.1.ffn_up.weight | 0x6d1fffa0 | 0x8180000 |
| 17 | blk.1.ffn_norm.weight | 0x7537ffa0 | 0x3800 |
| 18 | blk.1.attn_k.bias | 0x753837a0 | 0x800 |
| 19 | blk.1.attn_k.weight | 0x75383fa0 | 0x380000 |
| 20 | blk.1.attn_output.weight | 0x75703fa0 | 0x1880000 |
| 21 | blk.1.attn_q.bias | 0x76f83fa0 | 0x3800 |
| 22 | blk.1.attn_q.weight | 0x76f877a0 | 0x1880000 |
| 23 | blk.1.attn_v.bias | 0x788077a0 | 0x800 |
| 24 | blk.1.attn_v.weight | 0x78807fa0 | 0x380000 |
| 25 | blk.2.attn_norm.weight | 0x78b87fa0 | 0x3800 |
| 26 | blk.2.ffn_down.weight | 0x78b8b7a0 | 0x8180000 |
| 27 | blk.2.ffn_gate.weight | 0x80d0b7a0 | 0x8180000 |
| 28 | blk.2.ffn_up.weight | 0x88e8b7a0 | 0x8180000 |
| 29 | blk.2.ffn_norm.weight | 0x9100b7a0 | 0x3800 |
| 30 | blk.2.attn_k.bias | 0x9100efa0 | 0x800 |
| 31 | blk.2.attn_k.weight | 0x9100f7a0 | 0x380000 |
| 32 | blk.2.attn_output.weight | 0x9138f7a0 | 0x1880000 |
| 33 | blk.2.attn_q.bias | 0x92c0f7a0 | 0x3800 |
| 34 | blk.2.attn_q.weight | 0x92c12fa0 | 0x1880000 |
| 35 | blk.2.attn_v.bias | 0x94492fa0 | 0x800 |
| 36 | blk.2.attn_v.weight | 0x944937a0 | 0x380000 |
| 37 | blk.3.attn_norm.weight | 0x948137a0 | 0x3800 |
| 38 | blk.3.ffn_down.weight | 0x94816fa0 | 0x8180000 |
| 39 | blk.3.ffn_gate.weight | 0x9c996fa0 | 0x8180000 |
| 40 | blk.3.ffn_up.weight | 0xa4b16fa0 | 0x8180000 |
| 41 | blk.3.ffn_norm.weight | 0xacc96fa0 | 0x3800 |
| 42 | blk.3.attn_k.bias | 0xacc9a7a0 | 0x800 |
| 43 | blk.3.attn_k.weight | 0xacc9afa0 | 0x380000 |
| 44 | blk.3.attn_output.weight | 0xad01afa0 | 0x1880000 |
| 45 | blk.3.attn_q.bias | 0xae89afa0 | 0x3800 |
| 46 | blk.3.attn_q.weight | 0xae89e7a0 | 0x1880000 |
| 47 | blk.3.attn_v.bias | 0xb011e7a0 | 0x800 |
| 48 | blk.3.attn_v.weight | 0xb011efa0 | 0x380000 |
| 49 | blk.4.attn_norm.weight | 0xb049efa0 | 0x3800 |
| 50 | blk.4.ffn_down.weight | 0xb04a27a0 | 0x8180000 |
| 51 | blk.4.ffn_gate.weight | 0xb86227a0 | 0x8180000 |
| 52 | blk.4.ffn_up.weight | 0xc07a27a0 | 0x8180000 |
| 53 | blk.4.ffn_norm.weight | 0xc89227a0 | 0x3800 |
| 54 | blk.4.attn_k.bias | 0xc8925fa0 | 0x800 |
| 55 | blk.4.attn_k.weight | 0xc89267a0 | 0x380000 |
| 56 | blk.4.attn_output.weight | 0xc8ca67a0 | 0x1880000 |
| 57 | blk.4.attn_q.bias | 0xca5267a0 | 0x3800 |
| 58 | blk.4.attn_q.weight | 0xca529fa0 | 0x1880000 |
| 59 | blk.4.attn_v.bias | 0xcbda9fa0 | 0x800 |
| 60 | blk.4.attn_v.weight | 0xcbdaa7a0 | 0x380000 |
| 61 | blk.5.attn_norm.weight | 0xcc12a7a0 | 0x3800 |
| 62 | blk.5.ffn_down.weight | 0xcc12dfa0 | 0x8180000 |
| 63 | blk.5.ffn_gate.weight | 0xd42adfa0 | 0x8180000 |
| 64 | blk.5.ffn_up.weight | 0xdc42dfa0 | 0x8180000 |
| 65 | blk.5.ffn_norm.weight | 0xe45adfa0 | 0x3800 |
| 66 | blk.5.attn_k.bias | 0xe45b17a0 | 0x800 |
| 67 | blk.5.attn_k.weight | 0xe45b1fa0 | 0x380000 |
| 68 | blk.5.attn_output.weight | 0xe4931fa0 | 0x1880000 |
| 69 | blk.5.attn_q.bias | 0xe61b1fa0 | 0x3800 |
| 70 | blk.5.attn_q.weight | 0xe61b57a0 | 0x1880000 |
| 71 | blk.5.attn_v.bias | 0xe7a357a0 | 0x800 |
| 72 | blk.5.attn_v.weight | 0xe7a35fa0 | 0x380000 |
| 73 | blk.6.attn_norm.weight | 0xe7db5fa0 | 0x3800 |
| 74 | blk.6.ffn_down.weight | 0xe7db97a0 | 0x8180000 |
| 75 | blk.6.ffn_gate.weight | 0xeff397a0 | 0x8180000 |
| 76 | blk.6.ffn_up.weight | 0xf80b97a0 | 0x8180000 |
| 77 | blk.6.ffn_norm.weight | 0x1002397a0 | 0x3800 |
| 78 | blk.6.attn_k.bias | 0x10023cfa0 | 0x800 |
| 79 | blk.6.attn_k.weight | 0x10023d7a0 | 0x380000 |
| 80 | blk.6.attn_output.weight | 0x1005bd7a0 | 0x1880000 |
| 81 | blk.6.attn_q.bias | 0x101e3d7a0 | 0x3800 |
| 82 | blk.6.attn_q.weight | 0x101e40fa0 | 0x1880000 |
| 83 | blk.6.attn_v.bias | 0x1036c0fa0 | 0x800 |
| 84 | blk.6.attn_v.weight | 0x1036c17a0 | 0x380000 |
| 85 | blk.7.attn_norm.weight | 0x103a417a0 | 0x3800 |
| 86 | blk.7.ffn_down.weight | 0x103a44fa0 | 0x8180000 |
| 87 | blk.7.ffn_gate.weight | 0x10bbc4fa0 | 0x8180000 |
| 88 | blk.7.ffn_up.weight | 0x113d44fa0 | 0x8180000 |
| 89 | blk.7.ffn_norm.weight | 0x11bec4fa0 | 0x3800 |
| 90 | blk.7.attn_k.bias | 0x11bec87a0 | 0x800 |
| 91 | blk.7.attn_k.weight | 0x11bec8fa0 | 0x380000 |
| 92 | blk.7.attn_output.weight | 0x11c248fa0 | 0x1880000 |
| 93 | blk.7.attn_q.bias | 0x11dac8fa0 | 0x3800 |
| 94 | blk.7.attn_q.weight | 0x11dacc7a0 | 0x1880000 |
| 95 | blk.7.attn_v.bias | 0x11f34c7a0 | 0x800 |
| 96 | blk.7.attn_v.weight | 0x11f34cfa0 | 0x380000 |
| 97 | blk.8.attn_k.bias | 0x11f6ccfa0 | 0x800 |
| 98 | blk.8.attn_k.weight | 0x11f6cd7a0 | 0x380000 |
| 99 | blk.8.attn_output.weight | 0x11fa4d7a0 | 0x1880000 |
| 100 | blk.8.attn_q.bias | 0x1212cd7a0 | 0x3800 |
| 101 | blk.8.attn_q.weight | 0x1212d0fa0 | 0x1880000 |
| 102 | blk.8.attn_v.bias | 0x122b50fa0 | 0x800 |
| 103 | blk.8.attn_v.weight | 0x122b517a0 | 0x380000 |
| 104 | blk.10.attn_norm.weight | 0x122ed17a0 | 0x3800 |
| 105 | blk.10.ffn_down.weight | 0x122ed4fa0 | 0x8180000 |
| 106 | blk.10.ffn_gate.weight | 0x12b054fa0 | 0x8180000 |
| 107 | blk.10.ffn_up.weight | 0x1331d4fa0 | 0x8180000 |
| 108 | blk.10.ffn_norm.weight | 0x13b354fa0 | 0x3800 |
| 109 | blk.10.attn_k.bias | 0x13b3587a0 | 0x800 |
| 110 | blk.10.attn_k.weight | 0x13b358fa0 | 0x380000 |
| 111 | blk.10.attn_output.weight | 0x13b6d8fa0 | 0x1880000 |
| 112 | blk.10.attn_q.bias | 0x13cf58fa0 | 0x3800 |
| 113 | blk.10.attn_q.weight | 0x13cf5c7a0 | 0x1880000 |
| 114 | blk.10.attn_v.bias | 0x13e7dc7a0 | 0x800 |
| 115 | blk.10.attn_v.weight | 0x13e7dcfa0 | 0x380000 |
| 116 | blk.11.attn_norm.weight | 0x13eb5cfa0 | 0x3800 |
| 117 | blk.11.ffn_down.weight | 0x13eb607a0 | 0x8180000 |
| 118 | blk.11.ffn_gate.weight | 0x146ce07a0 | 0x8180000 |
| 119 | blk.11.ffn_up.weight | 0x14ee607a0 | 0x8180000 |
| 120 | blk.11.ffn_norm.weight | 0x156fe07a0 | 0x3800 |
| 121 | blk.11.attn_k.bias | 0x156fe3fa0 | 0x800 |
| 122 | blk.11.attn_k.weight | 0x156fe47a0 | 0x380000 |
| 123 | blk.11.attn_output.weight | 0x1573647a0 | 0x1880000 |
| 124 | blk.11.attn_q.bias | 0x158be47a0 | 0x3800 |
| 125 | blk.11.attn_q.weight | 0x158be7fa0 | 0x1880000 |
| 126 | blk.11.attn_v.bias | 0x15a467fa0 | 0x800 |
| 127 | blk.11.attn_v.weight | 0x15a4687a0 | 0x380000 |
| 128 | blk.12.attn_norm.weight | 0x15a7e87a0 | 0x3800 |
| 129 | blk.12.ffn_down.weight | 0x15a7ebfa0 | 0x8180000 |
| 130 | blk.12.ffn_gate.weight | 0x16296bfa0 | 0x8180000 |
| 131 | blk.12.ffn_up.weight | 0x16aaebfa0 | 0x8180000 |
| 132 | blk.12.ffn_norm.weight | 0x172c6bfa0 | 0x3800 |
| 133 | blk.12.attn_k.bias | 0x172c6f7a0 | 0x800 |
| 134 | blk.12.attn_k.weight | 0x172c6ffa0 | 0x380000 |
| 135 | blk.12.attn_output.weight | 0x172feffa0 | 0x1880000 |
| 136 | blk.12.attn_q.bias | 0x17486ffa0 | 0x3800 |
| 137 | blk.12.attn_q.weight | 0x1748737a0 | 0x1880000 |
| 138 | blk.12.attn_v.bias | 0x1760f37a0 | 0x800 |
| 139 | blk.12.attn_v.weight | 0x1760f3fa0 | 0x380000 |
| 140 | blk.13.attn_norm.weight | 0x176473fa0 | 0x3800 |
| 141 | blk.13.ffn_down.weight | 0x1764777a0 | 0x8180000 |
| 142 | blk.13.ffn_gate.weight | 0x17e5f77a0 | 0x8180000 |
| 143 | blk.13.ffn_up.weight | 0x1867777a0 | 0x8180000 |
| 144 | blk.13.ffn_norm.weight | 0x18e8f77a0 | 0x3800 |
| 145 | blk.13.attn_k.bias | 0x18e8fafa0 | 0x800 |
| 146 | blk.13.attn_k.weight | 0x18e8fb7a0 | 0x380000 |
| 147 | blk.13.attn_output.weight | 0x18ec7b7a0 | 0x1880000 |
| 148 | blk.13.attn_q.bias | 0x1904fb7a0 | 0x3800 |
| 149 | blk.13.attn_q.weight | 0x1904fefa0 | 0x1880000 |
| 150 | blk.13.attn_v.bias | 0x191d7efa0 | 0x800 |
| 151 | blk.13.attn_v.weight | 0x191d7f7a0 | 0x380000 |
| 152 | blk.14.attn_norm.weight | 0x1920ff7a0 | 0x3800 |
| 153 | blk.14.ffn_down.weight | 0x192102fa0 | 0x8180000 |
| 154 | blk.14.ffn_gate.weight | 0x19a282fa0 | 0x8180000 |
| 155 | blk.14.ffn_up.weight | 0x1a2402fa0 | 0x8180000 |
| 156 | blk.14.ffn_norm.weight | 0x1aa582fa0 | 0x3800 |
| 157 | blk.14.attn_k.bias | 0x1aa5867a0 | 0x800 |
| 158 | blk.14.attn_k.weight | 0x1aa586fa0 | 0x380000 |
| 159 | blk.14.attn_output.weight | 0x1aa906fa0 | 0x1880000 |
| 160 | blk.14.attn_q.bias | 0x1ac186fa0 | 0x3800 |
| 161 | blk.14.attn_q.weight | 0x1ac18a7a0 | 0x1880000 |
| 162 | blk.14.attn_v.bias | 0x1ada0a7a0 | 0x800 |
| 163 | blk.14.attn_v.weight | 0x1ada0afa0 | 0x380000 |
| 164 | blk.15.attn_norm.weight | 0x1add8afa0 | 0x3800 |
| 165 | blk.15.ffn_down.weight | 0x1add8e7a0 | 0x8180000 |
| 166 | blk.15.ffn_gate.weight | 0x1b5f0e7a0 | 0x8180000 |
| 167 | blk.15.ffn_up.weight | 0x1be08e7a0 | 0x8180000 |
| 168 | blk.15.ffn_norm.weight | 0x1c620e7a0 | 0x3800 |
| 169 | blk.15.attn_k.bias | 0x1c6211fa0 | 0x800 |
| 170 | blk.15.attn_k.weight | 0x1c62127a0 | 0x380000 |
| 171 | blk.15.attn_output.weight | 0x1c65927a0 | 0x1880000 |
| 172 | blk.15.attn_q.bias | 0x1c7e127a0 | 0x3800 |
| 173 | blk.15.attn_q.weight | 0x1c7e15fa0 | 0x1880000 |
| 174 | blk.15.attn_v.bias | 0x1c9695fa0 | 0x800 |
| 175 | blk.15.attn_v.weight | 0x1c96967a0 | 0x380000 |
| 176 | blk.16.attn_norm.weight | 0x1c9a167a0 | 0x3800 |
| 177 | blk.16.ffn_down.weight | 0x1c9a19fa0 | 0x8180000 |
| 178 | blk.16.ffn_gate.weight | 0x1d1b99fa0 | 0x8180000 |
| 179 | blk.16.ffn_up.weight | 0x1d9d19fa0 | 0x8180000 |
| 180 | blk.16.ffn_norm.weight | 0x1e1e99fa0 | 0x3800 |
| 181 | blk.16.attn_k.bias | 0x1e1e9d7a0 | 0x800 |
| 182 | blk.16.attn_k.weight | 0x1e1e9dfa0 | 0x380000 |
| 183 | blk.16.attn_output.weight | 0x1e221dfa0 | 0x1880000 |
| 184 | blk.16.attn_q.bias | 0x1e3a9dfa0 | 0x3800 |
| 185 | blk.16.attn_q.weight | 0x1e3aa17a0 | 0x1880000 |
| 186 | blk.16.attn_v.bias | 0x1e53217a0 | 0x800 |
| 187 | blk.16.attn_v.weight | 0x1e5321fa0 | 0x380000 |
| 188 | blk.17.attn_norm.weight | 0x1e56a1fa0 | 0x3800 |
| 189 | blk.17.ffn_down.weight | 0x1e56a57a0 | 0x8180000 |
| 190 | blk.17.ffn_gate.weight | 0x1ed8257a0 | 0x8180000 |
| 191 | blk.17.ffn_up.weight | 0x1f59a57a0 | 0x8180000 |
| 192 | blk.17.ffn_norm.weight | 0x1fdb257a0 | 0x3800 |
| 193 | blk.17.attn_k.bias | 0x1fdb28fa0 | 0x800 |
| 194 | blk.17.attn_k.weight | 0x1fdb297a0 | 0x380000 |
| 195 | blk.17.attn_output.weight | 0x1fdea97a0 | 0x1880000 |
| 196 | blk.17.attn_q.bias | 0x1ff7297a0 | 0x3800 |
| 197 | blk.17.attn_q.weight | 0x1ff72cfa0 | 0x1880000 |
| 198 | blk.17.attn_v.bias | 0x200facfa0 | 0x800 |
| 199 | blk.17.attn_v.weight | 0x200fad7a0 | 0x380000 |
| 200 | blk.18.ffn_gate.weight | 0x20132d7a0 | 0x8180000 |
| 201 | blk.18.ffn_up.weight | 0x2094ad7a0 | 0x8180000 |
| 202 | blk.18.attn_k.bias | 0x21162d7a0 | 0x800 |
| 203 | blk.18.attn_k.weight | 0x21162dfa0 | 0x380000 |
| 204 | blk.18.attn_output.weight | 0x2119adfa0 | 0x1880000 |
| 205 | blk.18.attn_q.bias | 0x21322dfa0 | 0x3800 |
| 206 | blk.18.attn_q.weight | 0x2132317a0 | 0x1880000 |
| 207 | blk.18.attn_v.bias | 0x214ab17a0 | 0x800 |
| 208 | blk.18.attn_v.weight | 0x214ab1fa0 | 0x380000 |
| 209 | blk.8.attn_norm.weight | 0x214e31fa0 | 0x3800 |
| 210 | blk.8.ffn_down.weight | 0x214e357a0 | 0x8180000 |
| 211 | blk.8.ffn_gate.weight | 0x21cfb57a0 | 0x8180000 |
| 212 | blk.8.ffn_up.weight | 0x2251357a0 | 0x8180000 |
| 213 | blk.8.ffn_norm.weight | 0x22d2b57a0 | 0x3800 |
| 214 | blk.9.attn_norm.weight | 0x22d2b8fa0 | 0x3800 |
| 215 | blk.9.ffn_down.weight | 0x22d2bc7a0 | 0x8180000 |
| 216 | blk.9.ffn_gate.weight | 0x23543c7a0 | 0x8180000 |
| 217 | blk.9.ffn_up.weight | 0x23d5bc7a0 | 0x8180000 |
| 218 | blk.9.ffn_norm.weight | 0x24573c7a0 | 0x3800 |
| 219 | blk.9.attn_k.bias | 0x24573ffa0 | 0x800 |
| 220 | blk.9.attn_k.weight | 0x2457407a0 | 0x380000 |
| 221 | blk.9.attn_output.weight | 0x245ac07a0 | 0x1880000 |
| 222 | blk.9.attn_q.bias | 0x2473407a0 | 0x3800 |
| 223 | blk.9.attn_q.weight | 0x247343fa0 | 0x1880000 |
| 224 | blk.9.attn_v.bias | 0x248bc3fa0 | 0x800 |
| 225 | blk.9.attn_v.weight | 0x248bc47a0 | 0x380000 |
| 226 | blk.18.attn_norm.weight | 0x248f447a0 | 0x3800 |
| 227 | blk.18.ffn_down.weight | 0x248f47fa0 | 0x8180000 |
| 228 | blk.18.ffn_norm.weight | 0x2510c7fa0 | 0x3800 |
| 229 | blk.19.attn_norm.weight | 0x2510cb7a0 | 0x3800 |
| 230 | blk.19.ffn_down.weight | 0x2510cefa0 | 0x8180000 |
| 231 | blk.19.ffn_gate.weight | 0x25924efa0 | 0x8180000 |
| 232 | blk.19.ffn_up.weight | 0x2613cefa0 | 0x8180000 |
| 233 | blk.19.ffn_norm.weight | 0x26954efa0 | 0x3800 |
| 234 | blk.19.attn_k.bias | 0x2695527a0 | 0x800 |
| 235 | blk.19.attn_k.weight | 0x269552fa0 | 0x380000 |
| 236 | blk.19.attn_output.weight | 0x2698d2fa0 | 0x1880000 |
| 237 | blk.19.attn_q.bias | 0x26b152fa0 | 0x3800 |
| 238 | blk.19.attn_q.weight | 0x26b1567a0 | 0x1880000 |
| 239 | blk.19.attn_v.bias | 0x26c9d67a0 | 0x800 |
| 240 | blk.19.attn_v.weight | 0x26c9d6fa0 | 0x380000 |
| 241 | blk.20.attn_norm.weight | 0x26cd56fa0 | 0x3800 |
| 242 | blk.20.ffn_down.weight | 0x26cd5a7a0 | 0x8180000 |
| 243 | blk.20.ffn_gate.weight | 0x274eda7a0 | 0x8180000 |
| 244 | blk.20.ffn_up.weight | 0x27d05a7a0 | 0x8180000 |
| 245 | blk.20.ffn_norm.weight | 0x2851da7a0 | 0x3800 |
| 246 | blk.20.attn_k.bias | 0x2851ddfa0 | 0x800 |
| 247 | blk.20.attn_k.weight | 0x2851de7a0 | 0x380000 |
| 248 | blk.20.attn_output.weight | 0x28555e7a0 | 0x1880000 |
| 249 | blk.20.attn_q.bias | 0x286dde7a0 | 0x3800 |
| 250 | blk.20.attn_q.weight | 0x286de1fa0 | 0x1880000 |
| 251 | blk.20.attn_v.bias | 0x288661fa0 | 0x800 |
| 252 | blk.20.attn_v.weight | 0x2886627a0 | 0x380000 |
| 253 | blk.21.attn_norm.weight | 0x2889e27a0 | 0x3800 |
| 254 | blk.21.ffn_down.weight | 0x2889e5fa0 | 0x8180000 |
| 255 | blk.21.ffn_gate.weight | 0x290b65fa0 | 0x8180000 |
| 256 | blk.21.ffn_up.weight | 0x298ce5fa0 | 0x8180000 |
| 257 | blk.21.ffn_norm.weight | 0x2a0e65fa0 | 0x3800 |
| 258 | blk.21.attn_k.bias | 0x2a0e697a0 | 0x800 |
| 259 | blk.21.attn_k.weight | 0x2a0e69fa0 | 0x380000 |
| 260 | blk.21.attn_output.weight | 0x2a11e9fa0 | 0x1880000 |
| 261 | blk.21.attn_q.bias | 0x2a2a69fa0 | 0x3800 |
| 262 | blk.21.attn_q.weight | 0x2a2a6d7a0 | 0x1880000 |
| 263 | blk.21.attn_v.bias | 0x2a42ed7a0 | 0x800 |
| 264 | blk.21.attn_v.weight | 0x2a42edfa0 | 0x380000 |
| 265 | blk.22.attn_norm.weight | 0x2a466dfa0 | 0x3800 |
| 266 | blk.22.ffn_down.weight | 0x2a46717a0 | 0x8180000 |
| 267 | blk.22.ffn_gate.weight | 0x2ac7f17a0 | 0x8180000 |
| 268 | blk.22.ffn_up.weight | 0x2b49717a0 | 0x8180000 |
| 269 | blk.22.ffn_norm.weight | 0x2bcaf17a0 | 0x3800 |
| 270 | blk.22.attn_k.bias | 0x2bcaf4fa0 | 0x800 |
| 271 | blk.22.attn_k.weight | 0x2bcaf57a0 | 0x380000 |
| 272 | blk.22.attn_output.weight | 0x2bce757a0 | 0x1880000 |
| 273 | blk.22.attn_q.bias | 0x2be6f57a0 | 0x3800 |
| 274 | blk.22.attn_q.weight | 0x2be6f8fa0 | 0x1880000 |
| 275 | blk.22.attn_v.bias | 0x2bff78fa0 | 0x800 |
| 276 | blk.22.attn_v.weight | 0x2bff797a0 | 0x380000 |
| 277 | blk.23.attn_norm.weight | 0x2c02f97a0 | 0x3800 |
| 278 | blk.23.ffn_down.weight | 0x2c02fcfa0 | 0x8180000 |
| 279 | blk.23.ffn_gate.weight | 0x2c847cfa0 | 0x8180000 |
| 280 | blk.23.ffn_up.weight | 0x2d05fcfa0 | 0x8180000 |
| 281 | blk.23.ffn_norm.weight | 0x2d877cfa0 | 0x3800 |
| 282 | blk.23.attn_k.bias | 0x2d87807a0 | 0x800 |
| 283 | blk.23.attn_k.weight | 0x2d8780fa0 | 0x380000 |
| 284 | blk.23.attn_output.weight | 0x2d8b00fa0 | 0x1880000 |
| 285 | blk.23.attn_q.bias | 0x2da380fa0 | 0x3800 |
| 286 | blk.23.attn_q.weight | 0x2da3847a0 | 0x1880000 |
| 287 | blk.23.attn_v.bias | 0x2dbc047a0 | 0x800 |
| 288 | blk.23.attn_v.weight | 0x2dbc04fa0 | 0x380000 |
| 289 | blk.24.attn_norm.weight | 0x2dbf84fa0 | 0x3800 |
| 290 | blk.24.ffn_down.weight | 0x2dbf887a0 | 0x8180000 |
| 291 | blk.24.ffn_gate.weight | 0x2e41087a0 | 0x8180000 |
| 292 | blk.24.ffn_up.weight | 0x2ec2887a0 | 0x8180000 |
| 293 | blk.24.ffn_norm.weight | 0x2f44087a0 | 0x3800 |
| 294 | blk.24.attn_k.bias | 0x2f440bfa0 | 0x800 |
| 295 | blk.24.attn_k.weight | 0x2f440c7a0 | 0x380000 |
| 296 | blk.24.attn_output.weight | 0x2f478c7a0 | 0x1880000 |
| 297 | blk.24.attn_q.bias | 0x2f600c7a0 | 0x3800 |
| 298 | blk.24.attn_q.weight | 0x2f600ffa0 | 0x1880000 |
| 299 | blk.24.attn_v.bias | 0x2f788ffa0 | 0x800 |
| 300 | blk.24.attn_v.weight | 0x2f78907a0 | 0x380000 |
| 301 | blk.25.attn_norm.weight | 0x2f7c107a0 | 0x3800 |
| 302 | blk.25.ffn_down.weight | 0x2f7c13fa0 | 0x8180000 |
| 303 | blk.25.ffn_gate.weight | 0x2ffd93fa0 | 0x8180000 |
| 304 | blk.25.ffn_up.weight | 0x307f13fa0 | 0x8180000 |
| 305 | blk.25.ffn_norm.weight | 0x310093fa0 | 0x3800 |
| 306 | blk.25.attn_k.bias | 0x3100977a0 | 0x800 |
| 307 | blk.25.attn_k.weight | 0x310097fa0 | 0x380000 |
| 308 | blk.25.attn_output.weight | 0x310417fa0 | 0x1880000 |
| 309 | blk.25.attn_q.bias | 0x311c97fa0 | 0x3800 |
| 310 | blk.25.attn_q.weight | 0x311c9b7a0 | 0x1880000 |
| 311 | blk.25.attn_v.bias | 0x31351b7a0 | 0x800 |
| 312 | blk.25.attn_v.weight | 0x31351bfa0 | 0x380000 |
| 313 | blk.26.attn_norm.weight | 0x31389bfa0 | 0x3800 |
| 314 | blk.26.ffn_down.weight | 0x31389f7a0 | 0x8180000 |
| 315 | blk.26.ffn_gate.weight | 0x31ba1f7a0 | 0x8180000 |
| 316 | blk.26.ffn_up.weight | 0x323b9f7a0 | 0x8180000 |
| 317 | blk.26.ffn_norm.weight | 0x32bd1f7a0 | 0x3800 |
| 318 | blk.26.attn_k.bias | 0x32bd22fa0 | 0x800 |
| 319 | blk.26.attn_k.weight | 0x32bd237a0 | 0x380000 |
| 320 | blk.26.attn_output.weight | 0x32c0a37a0 | 0x1880000 |
| 321 | blk.26.attn_q.bias | 0x32d9237a0 | 0x3800 |
| 322 | blk.26.attn_q.weight | 0x32d926fa0 | 0x1880000 |
| 323 | blk.26.attn_v.bias | 0x32f1a6fa0 | 0x800 |
| 324 | blk.26.attn_v.weight | 0x32f1a77a0 | 0x380000 |
| 325 | blk.27.attn_norm.weight | 0x32f5277a0 | 0x3800 |
| 326 | blk.27.ffn_down.weight | 0x32f52afa0 | 0x8180000 |
| 327 | blk.27.ffn_gate.weight | 0x3376aafa0 | 0x8180000 |
| 328 | blk.27.ffn_up.weight | 0x33f82afa0 | 0x8180000 |
| 329 | blk.27.ffn_norm.weight | 0x3479aafa0 | 0x3800 |
| 330 | blk.27.attn_k.bias | 0x3479ae7a0 | 0x800 |
| 331 | blk.27.attn_k.weight | 0x3479aefa0 | 0x380000 |
| 332 | blk.27.attn_output.weight | 0x347d2efa0 | 0x1880000 |
| 333 | blk.27.attn_q.bias | 0x3495aefa0 | 0x3800 |
| 334 | blk.27.attn_q.weight | 0x3495b27a0 | 0x1880000 |
| 335 | blk.27.attn_v.bias | 0x34ae327a0 | 0x800 |
| 336 | blk.27.attn_v.weight | 0x34ae32fa0 | 0x380000 |
| 337 | output_norm.weight | 0x34b1b2fa0 | 0x3800 |
| 338 | output.weight | 0x34b1b67a0 | 0x40cc5c00 |
### Base Tensor Group : ~1B Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
| 0 | token_embd.weight | Token Embedding (W) | (~544M) 543567360 | 3584 x 151665 x 1 x 1 | F16 |
| 337 | output_norm.weight | Output Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 338 | output.weight | Output (W) | (~544M) 543567360 | 3584 x 151665 x 1 x 1 | F16 |
- 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 |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 1 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 2 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 3 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 4 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 5 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 6 | blk.0.attn_k.bias | Block 0 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 7 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 8 | blk.0.attn_output.weight | Block 0 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 9 | blk.0.attn_q.bias | Block 0 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 10 | blk.0.attn_q.weight | Block 0 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 11 | blk.0.attn_v.bias | Block 0 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 12 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 13 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 14 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 15 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 16 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 17 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 18 | blk.1.attn_k.bias | Block 1 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 19 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 20 | blk.1.attn_output.weight | Block 1 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 21 | blk.1.attn_q.bias | Block 1 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 22 | blk.1.attn_q.weight | Block 1 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 23 | blk.1.attn_v.bias | Block 1 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 24 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 25 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 26 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 27 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 28 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 29 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 30 | blk.2.attn_k.bias | Block 2 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 31 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 32 | blk.2.attn_output.weight | Block 2 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 33 | blk.2.attn_q.bias | Block 2 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 34 | blk.2.attn_q.weight | Block 2 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 35 | blk.2.attn_v.bias | Block 2 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 36 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 37 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 38 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 39 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 40 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 41 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 42 | blk.3.attn_k.bias | Block 3 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 43 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 44 | blk.3.attn_output.weight | Block 3 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 45 | blk.3.attn_q.bias | Block 3 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 46 | blk.3.attn_q.weight | Block 3 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 47 | blk.3.attn_v.bias | Block 3 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 48 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 49 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 50 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 51 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 52 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 53 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 54 | blk.4.attn_k.bias | Block 4 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 55 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 56 | blk.4.attn_output.weight | Block 4 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 57 | blk.4.attn_q.bias | Block 4 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 58 | blk.4.attn_q.weight | Block 4 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 59 | blk.4.attn_v.bias | Block 4 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 60 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 61 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 62 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 63 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 64 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 65 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 66 | blk.5.attn_k.bias | Block 5 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 67 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 68 | blk.5.attn_output.weight | Block 5 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 69 | blk.5.attn_q.bias | Block 5 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 70 | blk.5.attn_q.weight | Block 5 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 71 | blk.5.attn_v.bias | Block 5 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 72 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 73 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 74 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 75 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 76 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 77 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 78 | blk.6.attn_k.bias | Block 6 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 79 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 80 | blk.6.attn_output.weight | Block 6 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 81 | blk.6.attn_q.bias | Block 6 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 82 | blk.6.attn_q.weight | Block 6 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 83 | blk.6.attn_v.bias | Block 6 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 84 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 85 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 86 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 87 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 88 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 89 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 90 | blk.7.attn_k.bias | Block 7 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 91 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 92 | blk.7.attn_output.weight | Block 7 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 93 | blk.7.attn_q.bias | Block 7 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 94 | blk.7.attn_q.weight | Block 7 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 95 | blk.7.attn_v.bias | Block 7 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 96 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 97 | blk.8.attn_k.bias | Block 8 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 98 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 99 | blk.8.attn_output.weight | Block 8 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 100 | blk.8.attn_q.bias | Block 8 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 101 | blk.8.attn_q.weight | Block 8 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 102 | blk.8.attn_v.bias | Block 8 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 103 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 209 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 210 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 211 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 212 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 213 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
- Total elements in blk.8: (~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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 104 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 105 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 106 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 107 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 108 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 109 | blk.10.attn_k.bias | Block 10 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 110 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 111 | blk.10.attn_output.weight | Block 10 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 112 | blk.10.attn_q.bias | Block 10 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 113 | blk.10.attn_q.weight | Block 10 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 114 | blk.10.attn_v.bias | Block 10 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 115 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 116 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 117 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 118 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 119 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 120 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 121 | blk.11.attn_k.bias | Block 11 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 122 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 123 | blk.11.attn_output.weight | Block 11 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 124 | blk.11.attn_q.bias | Block 11 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 125 | blk.11.attn_q.weight | Block 11 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 126 | blk.11.attn_v.bias | Block 11 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 127 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 128 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 129 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 130 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 131 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 132 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 133 | blk.12.attn_k.bias | Block 12 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 134 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 135 | blk.12.attn_output.weight | Block 12 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 136 | blk.12.attn_q.bias | Block 12 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 137 | blk.12.attn_q.weight | Block 12 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 138 | blk.12.attn_v.bias | Block 12 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 139 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 140 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 141 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 142 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 143 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 144 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 145 | blk.13.attn_k.bias | Block 13 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 146 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 147 | blk.13.attn_output.weight | Block 13 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 148 | blk.13.attn_q.bias | Block 13 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 149 | blk.13.attn_q.weight | Block 13 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 150 | blk.13.attn_v.bias | Block 13 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 151 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 152 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 153 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 154 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 155 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 156 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 157 | blk.14.attn_k.bias | Block 14 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 158 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 159 | blk.14.attn_output.weight | Block 14 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 160 | blk.14.attn_q.bias | Block 14 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 161 | blk.14.attn_q.weight | Block 14 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 162 | blk.14.attn_v.bias | Block 14 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 163 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 164 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 165 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 166 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 167 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 168 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 169 | blk.15.attn_k.bias | Block 15 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 170 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 171 | blk.15.attn_output.weight | Block 15 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 172 | blk.15.attn_q.bias | Block 15 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 173 | blk.15.attn_q.weight | Block 15 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 174 | blk.15.attn_v.bias | Block 15 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 175 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 176 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 177 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 178 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 179 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 180 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 181 | blk.16.attn_k.bias | Block 16 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 182 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 183 | blk.16.attn_output.weight | Block 16 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 184 | blk.16.attn_q.bias | Block 16 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 185 | blk.16.attn_q.weight | Block 16 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 186 | blk.16.attn_v.bias | Block 16 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 187 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 188 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 189 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 190 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 191 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 192 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 193 | blk.17.attn_k.bias | Block 17 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 194 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 195 | blk.17.attn_output.weight | Block 17 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 196 | blk.17.attn_q.bias | Block 17 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 197 | blk.17.attn_q.weight | Block 17 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 198 | blk.17.attn_v.bias | Block 17 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 199 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 200 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 201 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 202 | blk.18.attn_k.bias | Block 18 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 203 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 204 | blk.18.attn_output.weight | Block 18 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 205 | blk.18.attn_q.bias | Block 18 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 206 | blk.18.attn_q.weight | Block 18 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 207 | blk.18.attn_v.bias | Block 18 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 208 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 226 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 227 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 228 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
- Total elements in blk.18: (~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 |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 214 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 215 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 216 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 217 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 218 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 219 | blk.9.attn_k.bias | Block 9 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 220 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 221 | blk.9.attn_output.weight | Block 9 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 222 | blk.9.attn_q.bias | Block 9 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 223 | blk.9.attn_q.weight | Block 9 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 224 | blk.9.attn_v.bias | Block 9 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 225 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- Total elements in blk.9: (~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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 229 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 230 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 231 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 232 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 233 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 234 | blk.19.attn_k.bias | Block 19 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 235 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 236 | blk.19.attn_output.weight | Block 19 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 237 | blk.19.attn_q.bias | Block 19 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 238 | blk.19.attn_q.weight | Block 19 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 239 | blk.19.attn_v.bias | Block 19 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 240 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 241 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 242 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 243 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 244 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 245 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 246 | blk.20.attn_k.bias | Block 20 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 247 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 248 | blk.20.attn_output.weight | Block 20 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 249 | blk.20.attn_q.bias | Block 20 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 250 | blk.20.attn_q.weight | Block 20 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 251 | blk.20.attn_v.bias | Block 20 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 252 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 253 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 254 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 255 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 256 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 257 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 258 | blk.21.attn_k.bias | Block 21 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 259 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 260 | blk.21.attn_output.weight | Block 21 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 261 | blk.21.attn_q.bias | Block 21 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 262 | blk.21.attn_q.weight | Block 21 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 263 | blk.21.attn_v.bias | Block 21 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 264 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 265 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 266 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 267 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 268 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 269 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 270 | blk.22.attn_k.bias | Block 22 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 271 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 272 | blk.22.attn_output.weight | Block 22 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 273 | blk.22.attn_q.bias | Block 22 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 274 | blk.22.attn_q.weight | Block 22 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 275 | blk.22.attn_v.bias | Block 22 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 276 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 277 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 278 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 279 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 280 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 281 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 282 | blk.23.attn_k.bias | Block 23 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 283 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 284 | blk.23.attn_output.weight | Block 23 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 285 | blk.23.attn_q.bias | Block 23 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 286 | blk.23.attn_q.weight | Block 23 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 287 | blk.23.attn_v.bias | Block 23 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 288 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 289 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 290 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 291 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 292 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 293 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 294 | blk.24.attn_k.bias | Block 24 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 295 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 296 | blk.24.attn_output.weight | Block 24 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 297 | blk.24.attn_q.bias | Block 24 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 298 | blk.24.attn_q.weight | Block 24 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 299 | blk.24.attn_v.bias | Block 24 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 300 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 301 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 302 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 303 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 304 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 305 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 306 | blk.25.attn_k.bias | Block 25 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 307 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 308 | blk.25.attn_output.weight | Block 25 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 309 | blk.25.attn_q.bias | Block 25 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 310 | blk.25.attn_q.weight | Block 25 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 311 | blk.25.attn_v.bias | Block 25 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 312 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 313 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 314 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 315 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 316 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 317 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 318 | blk.26.attn_k.bias | Block 26 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 319 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 320 | blk.26.attn_output.weight | Block 26 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 321 | blk.26.attn_q.bias | Block 26 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 322 | blk.26.attn_q.weight | Block 26 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 323 | blk.26.attn_v.bias | Block 26 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 324 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- 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 |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 325 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 326 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~68M) 67895296 | 18944 x 3584 x 1 x 1 | F16 |
| 327 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 328 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~68M) 67895296 | 3584 x 18944 x 1 x 1 | F16 |
| 329 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 330 | blk.27.attn_k.bias | Block 27 Attention Key (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 331 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
| 332 | blk.27.attn_output.weight | Block 27 Attention Output (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 333 | blk.27.attn_q.bias | Block 27 Attention Query (B) | ( ~4K) 3584 | 3584 x 1 x 1 x 1 | F32 |
| 334 | blk.27.attn_q.weight | Block 27 Attention Query (W) | (~13M) 12845056 | 3584 x 3584 x 1 x 1 | F16 |
| 335 | blk.27.attn_v.bias | Block 27 Attention Value (B) | ( 512) 512 | 512 x 1 x 1 x 1 | F32 |
| 336 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~2M) 1835008 | 3584 x 512 x 1 x 1 | F16 |
- Total elements in blk.27: (~233M) 233057792
- Percentage of total elements: 3.06%