Mistral-Small-3.2-24B-Instruct-2506-pruned-GGUF
/
scores
/Mistral-Small-3.2-24B-Instruct-2506-pruned-F16.md
Mistral-Small-3.2-24B-Instruct-pruned-F16.gguf - GGUF Internal File Dump
- Endian: LITTLE endian
Key Value Metadata Store
There are 45 key-value pairs in this file
| POS | TYPE | Count | Key | Value |
|---|---|---|---|---|
| 1 | UINT32 | 1 | GGUF.version | 3 |
| 2 | UINT64 | 1 | GGUF.tensor_count | 345 |
| 3 | UINT64 | 1 | GGUF.kv_count | 42 |
| 4 | STRING | 1 | general.architecture | llama |
| 5 | STRING | 1 | general.type | model |
| 6 | STRING | 1 | general.name | Mistral Small 3.2 24B Instruct 2506 |
| 7 | STRING | 1 | general.version | 2506 |
| 8 | STRING | 1 | general.finetune | Instruct |
| 9 | STRING | 1 | general.basename | Mistral-Small-3.2 |
| 10 | STRING | 1 | general.size_label | 24B |
| 11 | STRING | 1 | general.license | apache-2.0 |
| 12 | UINT32 | 1 | general.base_model.count | 1 |
| 13 | STRING | 1 | general.base_model.0.name | Mistral Small 3.1 24B Base 2503 |
| 14 | STRING | 1 | general.base_model.0.version | 2503 |
| 15 | STRING | 1 | general.base_model.0.organization | Mistralai |
| 16 | STRING | 1 | general.base_model.0.repo_url | https://huggingface.co/mistral...istral-Small-3.1-24B-Base-2503 |
| 17 | [STRING] | 1 | general.tags | [ image-text-to-text ] |
| 18 | [STRING] | 24 | general.languages | [ en, fr, de, es, pt, ... ] |
| 19 | UINT32 | 1 | llama.context_length | 131072 |
| 20 | UINT32 | 1 | llama.embedding_length | 5120 |
| 21 | UINT32 | 1 | llama.feed_forward_length | 32768 |
| 22 | UINT32 | 1 | llama.attention.head_count | 32 |
| 23 | UINT32 | 1 | llama.attention.head_count_kv | 8 |
| 24 | FLOAT32 | 1 | llama.rope.freq_base | 1000000000.0 |
| 25 | FLOAT32 | 1 | llama.attention.layer_norm_rms_epsilon | 1e-05 |
| 26 | UINT32 | 1 | llama.attention.key_length | 128 |
| 27 | UINT32 | 1 | llama.attention.value_length | 128 |
| 28 | UINT32 | 1 | llama.vocab_size | 131072 |
| 29 | UINT32 | 1 | llama.rope.dimension_count | 128 |
| 30 | STRING | 1 | tokenizer.ggml.model | gpt2 |
| 31 | STRING | 1 | tokenizer.ggml.pre | tekken |
| 32 | [STRING] | 131072 | tokenizer.ggml.tokens | [ <unk>, <s>, </s>, [INST], [/INST], ... ] |
| 33 | [INT32] | 131072 | tokenizer.ggml.token_type | [ 3, 3, 3, 3, 3, 3, 3, ... ] |
| 34 | [STRING] | 269443 | tokenizer.ggml.merges | [ Ġ Ġ, Ġ t, e r, i n, Ġ ĠĠĠ, ... ] |
| 35 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 1 |
| 36 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 2 |
| 37 | UINT32 | 1 | tokenizer.ggml.unknown_token_id | 0 |
| 38 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 11 |
| 39 | BOOL | 1 | tokenizer.ggml.add_bos_token | True |
| 40 | BOOL | 1 | tokenizer.ggml.add_sep_token | False |
| 41 | BOOL | 1 | tokenizer.ggml.add_eos_token | False |
| 42 | BOOL | 1 | tokenizer.ggml.add_space_prefix | False |
| 43 | UINT32 | 1 | general.quantization_version | 2 |
| 44 | UINT32 | 1 | general.file_type | 1 |
| 45 | UINT32 | 1 | llama.block_count | 38 |
Tensors Overview ~22B Elements
Total number of elements in all tensors: 22460892160 Elements
- Mistral-Small-3.2-24B-Instruct-pruned-F16.gguf - GGUF Internal File Dump
- Key Value Metadata Store
- Tensors Overview ~22B Elements
- Tensor Data Offset
- Base Tensor Group : ~1B Elements
- Block 0 Tensor Group : ~556M Elements
- Block 1 Tensor Group : ~556M Elements
- Block 2 Tensor Group : ~556M Elements
- Block 3 Tensor Group : ~556M Elements
- Block 4 Tensor Group : ~556M Elements
- Block 5 Tensor Group : ~556M Elements
- Block 6 Tensor Group : ~556M Elements
- Block 7 Tensor Group : ~556M Elements
- Block 8 Tensor Group : ~556M Elements
- Block 9 Tensor Group : ~556M Elements
- Block 10 Tensor Group : ~556M Elements
- Block 11 Tensor Group : ~556M Elements
- Block 12 Tensor Group : ~556M Elements
- Block 13 Tensor Group : ~556M Elements
- Block 14 Tensor Group : ~556M Elements
- Block 15 Tensor Group : ~556M Elements
- Block 16 Tensor Group : ~556M Elements
- Block 17 Tensor Group : ~556M Elements
- Block 18 Tensor Group : ~556M Elements
- Block 19 Tensor Group : ~556M Elements
- Block 20 Tensor Group : ~556M Elements
- Block 21 Tensor Group : ~556M Elements
- Block 22 Tensor Group : ~556M Elements
- Block 23 Tensor Group : ~556M Elements
- Block 24 Tensor Group : ~556M Elements
- Block 25 Tensor Group : ~556M Elements
- Block 26 Tensor Group : ~556M Elements
- Block 27 Tensor Group : ~556M Elements
- Block 28 Tensor Group : ~556M Elements
- Block 29 Tensor Group : ~556M Elements
- Block 30 Tensor Group : ~556M Elements
- Block 31 Tensor Group : ~556M Elements
- Block 32 Tensor Group : ~556M Elements
- Block 33 Tensor Group : ~556M Elements
- Block 34 Tensor Group : ~556M Elements
- Block 35 Tensor Group : ~556M Elements
- Block 36 Tensor Group : ~556M Elements
- Block 37 Tensor Group : ~556M Elements
Tensor Data Offset
This table contains the offset and data segment relative to start of file
| T_ID | Tensor Layer Name | Data Offset (B) | Data Size (B) |
|---|---|---|---|
| 0 | output.weight | 0x7840e0 | 0x50000000 |
| 1 | output_norm.weight | 0x507840e0 | 0x5000 |
| 2 | token_embd.weight | 0x507890e0 | 0x50000000 |
| 3 | blk.0.attn_k.weight | 0xa07890e0 | 0xa00000 |
| 4 | blk.0.attn_norm.weight | 0xa11890e0 | 0x5000 |
| 5 | blk.0.attn_output.weight | 0xa118e0e0 | 0x2800000 |
| 6 | blk.0.attn_q.weight | 0xa398e0e0 | 0x2800000 |
| 7 | blk.0.attn_v.weight | 0xa618e0e0 | 0xa00000 |
| 8 | blk.0.ffn_down.weight | 0xa6b8e0e0 | 0x14000000 |
| 9 | blk.0.ffn_gate.weight | 0xbab8e0e0 | 0x14000000 |
| 10 | blk.0.ffn_norm.weight | 0xceb8e0e0 | 0x5000 |
| 11 | blk.0.ffn_up.weight | 0xceb930e0 | 0x14000000 |
| 12 | blk.1.attn_k.weight | 0xe2b930e0 | 0xa00000 |
| 13 | blk.1.attn_norm.weight | 0xe35930e0 | 0x5000 |
| 14 | blk.1.attn_output.weight | 0xe35980e0 | 0x2800000 |
| 15 | blk.1.attn_q.weight | 0xe5d980e0 | 0x2800000 |
| 16 | blk.1.attn_v.weight | 0xe85980e0 | 0xa00000 |
| 17 | blk.1.ffn_down.weight | 0xe8f980e0 | 0x14000000 |
| 18 | blk.1.ffn_gate.weight | 0xfcf980e0 | 0x14000000 |
| 19 | blk.1.ffn_norm.weight | 0x110f980e0 | 0x5000 |
| 20 | blk.1.ffn_up.weight | 0x110f9d0e0 | 0x14000000 |
| 21 | blk.2.attn_k.weight | 0x124f9d0e0 | 0xa00000 |
| 22 | blk.2.attn_norm.weight | 0x12599d0e0 | 0x5000 |
| 23 | blk.2.attn_output.weight | 0x1259a20e0 | 0x2800000 |
| 24 | blk.2.attn_q.weight | 0x1281a20e0 | 0x2800000 |
| 25 | blk.2.attn_v.weight | 0x12a9a20e0 | 0xa00000 |
| 26 | blk.2.ffn_down.weight | 0x12b3a20e0 | 0x14000000 |
| 27 | blk.2.ffn_gate.weight | 0x13f3a20e0 | 0x14000000 |
| 28 | blk.2.ffn_norm.weight | 0x1533a20e0 | 0x5000 |
| 29 | blk.2.ffn_up.weight | 0x1533a70e0 | 0x14000000 |
| 30 | blk.3.attn_k.weight | 0x1673a70e0 | 0xa00000 |
| 31 | blk.3.attn_norm.weight | 0x167da70e0 | 0x5000 |
| 32 | blk.3.attn_output.weight | 0x167dac0e0 | 0x2800000 |
| 33 | blk.3.attn_q.weight | 0x16a5ac0e0 | 0x2800000 |
| 34 | blk.3.attn_v.weight | 0x16cdac0e0 | 0xa00000 |
| 35 | blk.3.ffn_down.weight | 0x16d7ac0e0 | 0x14000000 |
| 36 | blk.3.ffn_gate.weight | 0x1817ac0e0 | 0x14000000 |
| 37 | blk.3.ffn_norm.weight | 0x1957ac0e0 | 0x5000 |
| 38 | blk.3.ffn_up.weight | 0x1957b10e0 | 0x14000000 |
| 39 | blk.4.attn_k.weight | 0x1a97b10e0 | 0xa00000 |
| 40 | blk.4.attn_norm.weight | 0x1aa1b10e0 | 0x5000 |
| 41 | blk.4.attn_output.weight | 0x1aa1b60e0 | 0x2800000 |
| 42 | blk.4.attn_q.weight | 0x1ac9b60e0 | 0x2800000 |
| 43 | blk.4.attn_v.weight | 0x1af1b60e0 | 0xa00000 |
| 44 | blk.4.ffn_down.weight | 0x1afbb60e0 | 0x14000000 |
| 45 | blk.4.ffn_gate.weight | 0x1c3bb60e0 | 0x14000000 |
| 46 | blk.4.ffn_norm.weight | 0x1d7bb60e0 | 0x5000 |
| 47 | blk.4.ffn_up.weight | 0x1d7bbb0e0 | 0x14000000 |
| 48 | blk.5.attn_k.weight | 0x1ebbbb0e0 | 0xa00000 |
| 49 | blk.5.attn_norm.weight | 0x1ec5bb0e0 | 0x5000 |
| 50 | blk.5.attn_output.weight | 0x1ec5c00e0 | 0x2800000 |
| 51 | blk.5.attn_q.weight | 0x1eedc00e0 | 0x2800000 |
| 52 | blk.5.attn_v.weight | 0x1f15c00e0 | 0xa00000 |
| 53 | blk.5.ffn_down.weight | 0x1f1fc00e0 | 0x14000000 |
| 54 | blk.5.ffn_gate.weight | 0x205fc00e0 | 0x14000000 |
| 55 | blk.5.ffn_norm.weight | 0x219fc00e0 | 0x5000 |
| 56 | blk.5.ffn_up.weight | 0x219fc50e0 | 0x14000000 |
| 57 | blk.6.attn_k.weight | 0x22dfc50e0 | 0xa00000 |
| 58 | blk.6.attn_norm.weight | 0x22e9c50e0 | 0x5000 |
| 59 | blk.6.attn_output.weight | 0x22e9ca0e0 | 0x2800000 |
| 60 | blk.6.attn_q.weight | 0x2311ca0e0 | 0x2800000 |
| 61 | blk.6.attn_v.weight | 0x2339ca0e0 | 0xa00000 |
| 62 | blk.6.ffn_down.weight | 0x2343ca0e0 | 0x14000000 |
| 63 | blk.6.ffn_gate.weight | 0x2483ca0e0 | 0x14000000 |
| 64 | blk.6.ffn_norm.weight | 0x25c3ca0e0 | 0x5000 |
| 65 | blk.6.ffn_up.weight | 0x25c3cf0e0 | 0x14000000 |
| 66 | blk.7.attn_k.weight | 0x2703cf0e0 | 0xa00000 |
| 67 | blk.7.attn_norm.weight | 0x270dcf0e0 | 0x5000 |
| 68 | blk.7.attn_output.weight | 0x270dd40e0 | 0x2800000 |
| 69 | blk.7.attn_q.weight | 0x2735d40e0 | 0x2800000 |
| 70 | blk.7.attn_v.weight | 0x275dd40e0 | 0xa00000 |
| 71 | blk.7.ffn_down.weight | 0x2767d40e0 | 0x14000000 |
| 72 | blk.7.ffn_gate.weight | 0x28a7d40e0 | 0x14000000 |
| 73 | blk.7.ffn_norm.weight | 0x29e7d40e0 | 0x5000 |
| 74 | blk.7.ffn_up.weight | 0x29e7d90e0 | 0x14000000 |
| 75 | blk.8.attn_k.weight | 0x2b27d90e0 | 0xa00000 |
| 76 | blk.8.attn_norm.weight | 0x2b31d90e0 | 0x5000 |
| 77 | blk.8.attn_output.weight | 0x2b31de0e0 | 0x2800000 |
| 78 | blk.8.attn_q.weight | 0x2b59de0e0 | 0x2800000 |
| 79 | blk.8.attn_v.weight | 0x2b81de0e0 | 0xa00000 |
| 80 | blk.8.ffn_down.weight | 0x2b8bde0e0 | 0x14000000 |
| 81 | blk.8.ffn_gate.weight | 0x2ccbde0e0 | 0x14000000 |
| 82 | blk.8.ffn_norm.weight | 0x2e0bde0e0 | 0x5000 |
| 83 | blk.8.ffn_up.weight | 0x2e0be30e0 | 0x14000000 |
| 84 | blk.9.attn_k.weight | 0x2f4be30e0 | 0xa00000 |
| 85 | blk.9.attn_norm.weight | 0x2f55e30e0 | 0x5000 |
| 86 | blk.9.attn_output.weight | 0x2f55e80e0 | 0x2800000 |
| 87 | blk.9.attn_q.weight | 0x2f7de80e0 | 0x2800000 |
| 88 | blk.9.attn_v.weight | 0x2fa5e80e0 | 0xa00000 |
| 89 | blk.9.ffn_down.weight | 0x2fafe80e0 | 0x14000000 |
| 90 | blk.9.ffn_gate.weight | 0x30efe80e0 | 0x14000000 |
| 91 | blk.9.ffn_norm.weight | 0x322fe80e0 | 0x5000 |
| 92 | blk.9.ffn_up.weight | 0x322fed0e0 | 0x14000000 |
| 93 | blk.10.attn_k.weight | 0x336fed0e0 | 0xa00000 |
| 94 | blk.10.attn_norm.weight | 0x3379ed0e0 | 0x5000 |
| 95 | blk.10.attn_output.weight | 0x3379f20e0 | 0x2800000 |
| 96 | blk.10.attn_q.weight | 0x33a1f20e0 | 0x2800000 |
| 97 | blk.10.attn_v.weight | 0x33c9f20e0 | 0xa00000 |
| 98 | blk.10.ffn_down.weight | 0x33d3f20e0 | 0x14000000 |
| 99 | blk.10.ffn_gate.weight | 0x3513f20e0 | 0x14000000 |
| 100 | blk.10.ffn_norm.weight | 0x3653f20e0 | 0x5000 |
| 101 | blk.10.ffn_up.weight | 0x3653f70e0 | 0x14000000 |
| 102 | blk.11.attn_k.weight | 0x3793f70e0 | 0xa00000 |
| 103 | blk.11.attn_norm.weight | 0x379df70e0 | 0x5000 |
| 104 | blk.11.attn_output.weight | 0x379dfc0e0 | 0x2800000 |
| 105 | blk.11.attn_q.weight | 0x37c5fc0e0 | 0x2800000 |
| 106 | blk.11.attn_v.weight | 0x37edfc0e0 | 0xa00000 |
| 107 | blk.11.ffn_down.weight | 0x37f7fc0e0 | 0x14000000 |
| 108 | blk.11.ffn_gate.weight | 0x3937fc0e0 | 0x14000000 |
| 109 | blk.11.ffn_norm.weight | 0x3a77fc0e0 | 0x5000 |
| 110 | blk.11.ffn_up.weight | 0x3a78010e0 | 0x14000000 |
| 111 | blk.12.attn_k.weight | 0x3bb8010e0 | 0xa00000 |
| 112 | blk.12.attn_norm.weight | 0x3bc2010e0 | 0x5000 |
| 113 | blk.12.attn_output.weight | 0x3bc2060e0 | 0x2800000 |
| 114 | blk.12.attn_q.weight | 0x3bea060e0 | 0x2800000 |
| 115 | blk.12.attn_v.weight | 0x3c12060e0 | 0xa00000 |
| 116 | blk.12.ffn_down.weight | 0x3c1c060e0 | 0x14000000 |
| 117 | blk.12.ffn_gate.weight | 0x3d5c060e0 | 0x14000000 |
| 118 | blk.12.ffn_norm.weight | 0x3e9c060e0 | 0x5000 |
| 119 | blk.12.ffn_up.weight | 0x3e9c0b0e0 | 0x14000000 |
| 120 | blk.13.attn_k.weight | 0x3fdc0b0e0 | 0xa00000 |
| 121 | blk.13.attn_norm.weight | 0x3fe60b0e0 | 0x5000 |
| 122 | blk.13.attn_output.weight | 0x3fe6100e0 | 0x2800000 |
| 123 | blk.13.attn_q.weight | 0x400e100e0 | 0x2800000 |
| 124 | blk.13.attn_v.weight | 0x4036100e0 | 0xa00000 |
| 125 | blk.13.ffn_down.weight | 0x4040100e0 | 0x14000000 |
| 126 | blk.13.ffn_gate.weight | 0x4180100e0 | 0x14000000 |
| 127 | blk.13.ffn_norm.weight | 0x42c0100e0 | 0x5000 |
| 128 | blk.13.ffn_up.weight | 0x42c0150e0 | 0x14000000 |
| 129 | blk.14.attn_k.weight | 0x4400150e0 | 0xa00000 |
| 130 | blk.14.attn_norm.weight | 0x440a150e0 | 0x5000 |
| 131 | blk.14.attn_output.weight | 0x440a1a0e0 | 0x2800000 |
| 132 | blk.14.attn_q.weight | 0x44321a0e0 | 0x2800000 |
| 133 | blk.14.attn_v.weight | 0x445a1a0e0 | 0xa00000 |
| 134 | blk.14.ffn_down.weight | 0x44641a0e0 | 0x14000000 |
| 135 | blk.14.ffn_gate.weight | 0x45a41a0e0 | 0x14000000 |
| 136 | blk.14.ffn_norm.weight | 0x46e41a0e0 | 0x5000 |
| 137 | blk.14.ffn_up.weight | 0x46e41f0e0 | 0x14000000 |
| 138 | blk.15.attn_k.weight | 0x48241f0e0 | 0xa00000 |
| 139 | blk.15.attn_norm.weight | 0x482e1f0e0 | 0x5000 |
| 140 | blk.15.attn_output.weight | 0x482e240e0 | 0x2800000 |
| 141 | blk.15.attn_q.weight | 0x4856240e0 | 0x2800000 |
| 142 | blk.15.attn_v.weight | 0x487e240e0 | 0xa00000 |
| 143 | blk.15.ffn_down.weight | 0x4888240e0 | 0x14000000 |
| 144 | blk.15.ffn_gate.weight | 0x49c8240e0 | 0x14000000 |
| 145 | blk.15.ffn_norm.weight | 0x4b08240e0 | 0x5000 |
| 146 | blk.15.ffn_up.weight | 0x4b08290e0 | 0x14000000 |
| 147 | blk.16.attn_k.weight | 0x4c48290e0 | 0xa00000 |
| 148 | blk.16.attn_norm.weight | 0x4c52290e0 | 0x5000 |
| 149 | blk.16.attn_output.weight | 0x4c522e0e0 | 0x2800000 |
| 150 | blk.16.attn_q.weight | 0x4c7a2e0e0 | 0x2800000 |
| 151 | blk.16.attn_v.weight | 0x4ca22e0e0 | 0xa00000 |
| 152 | blk.16.ffn_down.weight | 0x4cac2e0e0 | 0x14000000 |
| 153 | blk.16.ffn_gate.weight | 0x4dec2e0e0 | 0x14000000 |
| 154 | blk.16.ffn_norm.weight | 0x4f2c2e0e0 | 0x5000 |
| 155 | blk.16.ffn_up.weight | 0x4f2c330e0 | 0x14000000 |
| 156 | blk.17.attn_k.weight | 0x506c330e0 | 0xa00000 |
| 157 | blk.17.attn_norm.weight | 0x5076330e0 | 0x5000 |
| 158 | blk.17.attn_output.weight | 0x5076380e0 | 0x2800000 |
| 159 | blk.17.attn_q.weight | 0x509e380e0 | 0x2800000 |
| 160 | blk.17.attn_v.weight | 0x50c6380e0 | 0xa00000 |
| 161 | blk.17.ffn_down.weight | 0x50d0380e0 | 0x14000000 |
| 162 | blk.17.ffn_gate.weight | 0x5210380e0 | 0x14000000 |
| 163 | blk.17.ffn_norm.weight | 0x5350380e0 | 0x5000 |
| 164 | blk.17.ffn_up.weight | 0x53503d0e0 | 0x14000000 |
| 165 | blk.18.attn_k.weight | 0x54903d0e0 | 0xa00000 |
| 166 | blk.18.attn_norm.weight | 0x549a3d0e0 | 0x5000 |
| 167 | blk.18.attn_output.weight | 0x549a420e0 | 0x2800000 |
| 168 | blk.18.attn_q.weight | 0x54c2420e0 | 0x2800000 |
| 169 | blk.18.attn_v.weight | 0x54ea420e0 | 0xa00000 |
| 170 | blk.18.ffn_down.weight | 0x54f4420e0 | 0x14000000 |
| 171 | blk.18.ffn_gate.weight | 0x5634420e0 | 0x14000000 |
| 172 | blk.18.ffn_norm.weight | 0x5774420e0 | 0x5000 |
| 173 | blk.18.ffn_up.weight | 0x5774470e0 | 0x14000000 |
| 174 | blk.19.attn_k.weight | 0x58b4470e0 | 0xa00000 |
| 175 | blk.19.attn_norm.weight | 0x58be470e0 | 0x5000 |
| 176 | blk.19.attn_output.weight | 0x58be4c0e0 | 0x2800000 |
| 177 | blk.19.attn_q.weight | 0x58e64c0e0 | 0x2800000 |
| 178 | blk.19.attn_v.weight | 0x590e4c0e0 | 0xa00000 |
| 179 | blk.19.ffn_down.weight | 0x59184c0e0 | 0x14000000 |
| 180 | blk.19.ffn_gate.weight | 0x5a584c0e0 | 0x14000000 |
| 181 | blk.19.ffn_norm.weight | 0x5b984c0e0 | 0x5000 |
| 182 | blk.19.ffn_up.weight | 0x5b98510e0 | 0x14000000 |
| 183 | blk.20.attn_k.weight | 0x5cd8510e0 | 0xa00000 |
| 184 | blk.20.attn_norm.weight | 0x5ce2510e0 | 0x5000 |
| 185 | blk.20.attn_output.weight | 0x5ce2560e0 | 0x2800000 |
| 186 | blk.20.attn_q.weight | 0x5d0a560e0 | 0x2800000 |
| 187 | blk.20.attn_v.weight | 0x5d32560e0 | 0xa00000 |
| 188 | blk.20.ffn_down.weight | 0x5d3c560e0 | 0x14000000 |
| 189 | blk.20.ffn_gate.weight | 0x5e7c560e0 | 0x14000000 |
| 190 | blk.20.ffn_norm.weight | 0x5fbc560e0 | 0x5000 |
| 191 | blk.20.ffn_up.weight | 0x5fbc5b0e0 | 0x14000000 |
| 192 | blk.21.attn_k.weight | 0x60fc5b0e0 | 0xa00000 |
| 193 | blk.21.attn_norm.weight | 0x61065b0e0 | 0x5000 |
| 194 | blk.21.attn_output.weight | 0x6106600e0 | 0x2800000 |
| 195 | blk.21.attn_q.weight | 0x612e600e0 | 0x2800000 |
| 196 | blk.21.attn_v.weight | 0x6156600e0 | 0xa00000 |
| 197 | blk.21.ffn_down.weight | 0x6160600e0 | 0x14000000 |
| 198 | blk.21.ffn_gate.weight | 0x62a0600e0 | 0x14000000 |
| 199 | blk.21.ffn_norm.weight | 0x63e0600e0 | 0x5000 |
| 200 | blk.21.ffn_up.weight | 0x63e0650e0 | 0x14000000 |
| 201 | blk.22.attn_k.weight | 0x6520650e0 | 0xa00000 |
| 202 | blk.22.attn_norm.weight | 0x652a650e0 | 0x5000 |
| 203 | blk.22.attn_output.weight | 0x652a6a0e0 | 0x2800000 |
| 204 | blk.22.attn_q.weight | 0x65526a0e0 | 0x2800000 |
| 205 | blk.22.attn_v.weight | 0x657a6a0e0 | 0xa00000 |
| 206 | blk.22.ffn_down.weight | 0x65846a0e0 | 0x14000000 |
| 207 | blk.22.ffn_gate.weight | 0x66c46a0e0 | 0x14000000 |
| 208 | blk.22.ffn_norm.weight | 0x68046a0e0 | 0x5000 |
| 209 | blk.22.ffn_up.weight | 0x68046f0e0 | 0x14000000 |
| 210 | blk.23.attn_k.weight | 0x69446f0e0 | 0xa00000 |
| 211 | blk.23.attn_norm.weight | 0x694e6f0e0 | 0x5000 |
| 212 | blk.23.attn_output.weight | 0x694e740e0 | 0x2800000 |
| 213 | blk.23.attn_q.weight | 0x6976740e0 | 0x2800000 |
| 214 | blk.23.attn_v.weight | 0x699e740e0 | 0xa00000 |
| 215 | blk.23.ffn_down.weight | 0x69a8740e0 | 0x14000000 |
| 216 | blk.23.ffn_gate.weight | 0x6ae8740e0 | 0x14000000 |
| 217 | blk.23.ffn_norm.weight | 0x6c28740e0 | 0x5000 |
| 218 | blk.23.ffn_up.weight | 0x6c28790e0 | 0x14000000 |
| 219 | blk.24.attn_k.weight | 0x6d68790e0 | 0xa00000 |
| 220 | blk.24.attn_norm.weight | 0x6d72790e0 | 0x5000 |
| 221 | blk.24.attn_output.weight | 0x6d727e0e0 | 0x2800000 |
| 222 | blk.24.attn_q.weight | 0x6d9a7e0e0 | 0x2800000 |
| 223 | blk.24.attn_v.weight | 0x6dc27e0e0 | 0xa00000 |
| 224 | blk.24.ffn_down.weight | 0x6dcc7e0e0 | 0x14000000 |
| 225 | blk.24.ffn_gate.weight | 0x6f0c7e0e0 | 0x14000000 |
| 226 | blk.24.ffn_norm.weight | 0x704c7e0e0 | 0x5000 |
| 227 | blk.24.ffn_up.weight | 0x704c830e0 | 0x14000000 |
| 228 | blk.25.attn_k.weight | 0x718c830e0 | 0xa00000 |
| 229 | blk.25.attn_norm.weight | 0x7196830e0 | 0x5000 |
| 230 | blk.25.attn_output.weight | 0x7196880e0 | 0x2800000 |
| 231 | blk.25.attn_q.weight | 0x71be880e0 | 0x2800000 |
| 232 | blk.25.attn_v.weight | 0x71e6880e0 | 0xa00000 |
| 233 | blk.25.ffn_down.weight | 0x71f0880e0 | 0x14000000 |
| 234 | blk.25.ffn_gate.weight | 0x7330880e0 | 0x14000000 |
| 235 | blk.25.ffn_norm.weight | 0x7470880e0 | 0x5000 |
| 236 | blk.25.ffn_up.weight | 0x74708d0e0 | 0x14000000 |
| 237 | blk.26.attn_k.weight | 0x75b08d0e0 | 0xa00000 |
| 238 | blk.26.attn_norm.weight | 0x75ba8d0e0 | 0x5000 |
| 239 | blk.26.attn_output.weight | 0x75ba920e0 | 0x2800000 |
| 240 | blk.26.attn_q.weight | 0x75e2920e0 | 0x2800000 |
| 241 | blk.26.attn_v.weight | 0x760a920e0 | 0xa00000 |
| 242 | blk.26.ffn_down.weight | 0x7614920e0 | 0x14000000 |
| 243 | blk.26.ffn_gate.weight | 0x7754920e0 | 0x14000000 |
| 244 | blk.26.ffn_norm.weight | 0x7894920e0 | 0x5000 |
| 245 | blk.26.ffn_up.weight | 0x7894970e0 | 0x14000000 |
| 246 | blk.27.attn_k.weight | 0x79d4970e0 | 0xa00000 |
| 247 | blk.27.attn_norm.weight | 0x79de970e0 | 0x5000 |
| 248 | blk.27.attn_output.weight | 0x79de9c0e0 | 0x2800000 |
| 249 | blk.27.attn_q.weight | 0x7a069c0e0 | 0x2800000 |
| 250 | blk.27.attn_v.weight | 0x7a2e9c0e0 | 0xa00000 |
| 251 | blk.27.ffn_down.weight | 0x7a389c0e0 | 0x14000000 |
| 252 | blk.27.ffn_gate.weight | 0x7b789c0e0 | 0x14000000 |
| 253 | blk.27.ffn_norm.weight | 0x7cb89c0e0 | 0x5000 |
| 254 | blk.27.ffn_up.weight | 0x7cb8a10e0 | 0x14000000 |
| 255 | blk.28.attn_k.weight | 0x7df8a10e0 | 0xa00000 |
| 256 | blk.28.attn_norm.weight | 0x7e02a10e0 | 0x5000 |
| 257 | blk.28.attn_output.weight | 0x7e02a60e0 | 0x2800000 |
| 258 | blk.28.attn_q.weight | 0x7e2aa60e0 | 0x2800000 |
| 259 | blk.28.attn_v.weight | 0x7e52a60e0 | 0xa00000 |
| 260 | blk.28.ffn_down.weight | 0x7e5ca60e0 | 0x14000000 |
| 261 | blk.28.ffn_gate.weight | 0x7f9ca60e0 | 0x14000000 |
| 262 | blk.28.ffn_norm.weight | 0x80dca60e0 | 0x5000 |
| 263 | blk.28.ffn_up.weight | 0x80dcab0e0 | 0x14000000 |
| 264 | blk.29.attn_k.weight | 0x821cab0e0 | 0xa00000 |
| 265 | blk.29.attn_norm.weight | 0x8226ab0e0 | 0x5000 |
| 266 | blk.29.attn_output.weight | 0x8226b00e0 | 0x2800000 |
| 267 | blk.29.attn_q.weight | 0x824eb00e0 | 0x2800000 |
| 268 | blk.29.attn_v.weight | 0x8276b00e0 | 0xa00000 |
| 269 | blk.29.ffn_down.weight | 0x8280b00e0 | 0x14000000 |
| 270 | blk.29.ffn_gate.weight | 0x83c0b00e0 | 0x14000000 |
| 271 | blk.29.ffn_norm.weight | 0x8500b00e0 | 0x5000 |
| 272 | blk.29.ffn_up.weight | 0x8500b50e0 | 0x14000000 |
| 273 | blk.30.attn_k.weight | 0x8640b50e0 | 0xa00000 |
| 274 | blk.30.attn_norm.weight | 0x864ab50e0 | 0x5000 |
| 275 | blk.30.attn_output.weight | 0x864aba0e0 | 0x2800000 |
| 276 | blk.30.attn_q.weight | 0x8672ba0e0 | 0x2800000 |
| 277 | blk.30.attn_v.weight | 0x869aba0e0 | 0xa00000 |
| 278 | blk.30.ffn_down.weight | 0x86a4ba0e0 | 0x14000000 |
| 279 | blk.30.ffn_gate.weight | 0x87e4ba0e0 | 0x14000000 |
| 280 | blk.30.ffn_norm.weight | 0x8924ba0e0 | 0x5000 |
| 281 | blk.30.ffn_up.weight | 0x8924bf0e0 | 0x14000000 |
| 282 | blk.31.attn_k.weight | 0x8a64bf0e0 | 0xa00000 |
| 283 | blk.31.attn_norm.weight | 0x8a6ebf0e0 | 0x5000 |
| 284 | blk.31.attn_output.weight | 0x8a6ec40e0 | 0x2800000 |
| 285 | blk.31.attn_q.weight | 0x8a96c40e0 | 0x2800000 |
| 286 | blk.31.attn_v.weight | 0x8abec40e0 | 0xa00000 |
| 287 | blk.31.ffn_down.weight | 0x8ac8c40e0 | 0x14000000 |
| 288 | blk.31.ffn_gate.weight | 0x8c08c40e0 | 0x14000000 |
| 289 | blk.31.ffn_norm.weight | 0x8d48c40e0 | 0x5000 |
| 290 | blk.31.ffn_up.weight | 0x8d48c90e0 | 0x14000000 |
| 291 | blk.32.attn_k.weight | 0x8e88c90e0 | 0xa00000 |
| 292 | blk.32.attn_norm.weight | 0x8e92c90e0 | 0x5000 |
| 293 | blk.32.attn_output.weight | 0x8e92ce0e0 | 0x2800000 |
| 294 | blk.32.attn_q.weight | 0x8ebace0e0 | 0x2800000 |
| 295 | blk.32.attn_v.weight | 0x8ee2ce0e0 | 0xa00000 |
| 296 | blk.32.ffn_down.weight | 0x8eecce0e0 | 0x14000000 |
| 297 | blk.32.ffn_gate.weight | 0x902cce0e0 | 0x14000000 |
| 298 | blk.32.ffn_norm.weight | 0x916cce0e0 | 0x5000 |
| 299 | blk.32.ffn_up.weight | 0x916cd30e0 | 0x14000000 |
| 300 | blk.33.attn_k.weight | 0x92acd30e0 | 0xa00000 |
| 301 | blk.33.attn_norm.weight | 0x92b6d30e0 | 0x5000 |
| 302 | blk.33.attn_output.weight | 0x92b6d80e0 | 0x2800000 |
| 303 | blk.33.attn_q.weight | 0x92ded80e0 | 0x2800000 |
| 304 | blk.33.attn_v.weight | 0x9306d80e0 | 0xa00000 |
| 305 | blk.33.ffn_down.weight | 0x9310d80e0 | 0x14000000 |
| 306 | blk.33.ffn_gate.weight | 0x9450d80e0 | 0x14000000 |
| 307 | blk.33.ffn_norm.weight | 0x9590d80e0 | 0x5000 |
| 308 | blk.33.ffn_up.weight | 0x9590dd0e0 | 0x14000000 |
| 309 | blk.34.attn_k.weight | 0x96d0dd0e0 | 0xa00000 |
| 310 | blk.34.attn_norm.weight | 0x96dadd0e0 | 0x5000 |
| 311 | blk.34.attn_output.weight | 0x96dae20e0 | 0x2800000 |
| 312 | blk.34.attn_q.weight | 0x9702e20e0 | 0x2800000 |
| 313 | blk.34.attn_v.weight | 0x972ae20e0 | 0xa00000 |
| 314 | blk.34.ffn_down.weight | 0x9734e20e0 | 0x14000000 |
| 315 | blk.34.ffn_gate.weight | 0x9874e20e0 | 0x14000000 |
| 316 | blk.34.ffn_norm.weight | 0x99b4e20e0 | 0x5000 |
| 317 | blk.34.ffn_up.weight | 0x99b4e70e0 | 0x14000000 |
| 318 | blk.35.attn_k.weight | 0x9af4e70e0 | 0xa00000 |
| 319 | blk.35.attn_norm.weight | 0x9afee70e0 | 0x5000 |
| 320 | blk.35.attn_output.weight | 0x9afeec0e0 | 0x2800000 |
| 321 | blk.35.attn_q.weight | 0x9b26ec0e0 | 0x2800000 |
| 322 | blk.35.attn_v.weight | 0x9b4eec0e0 | 0xa00000 |
| 323 | blk.35.ffn_down.weight | 0x9b58ec0e0 | 0x14000000 |
| 324 | blk.35.ffn_gate.weight | 0x9c98ec0e0 | 0x14000000 |
| 325 | blk.35.ffn_norm.weight | 0x9dd8ec0e0 | 0x5000 |
| 326 | blk.35.ffn_up.weight | 0x9dd8f10e0 | 0x14000000 |
| 327 | blk.36.attn_k.weight | 0x9f18f10e0 | 0xa00000 |
| 328 | blk.36.attn_norm.weight | 0x9f22f10e0 | 0x5000 |
| 329 | blk.36.attn_output.weight | 0x9f22f60e0 | 0x2800000 |
| 330 | blk.36.attn_q.weight | 0x9f4af60e0 | 0x2800000 |
| 331 | blk.36.attn_v.weight | 0x9f72f60e0 | 0xa00000 |
| 332 | blk.36.ffn_down.weight | 0x9f7cf60e0 | 0x14000000 |
| 333 | blk.36.ffn_gate.weight | 0xa0bcf60e0 | 0x14000000 |
| 334 | blk.36.ffn_norm.weight | 0xa1fcf60e0 | 0x5000 |
| 335 | blk.36.ffn_up.weight | 0xa1fcfb0e0 | 0x14000000 |
| 336 | blk.37.attn_k.weight | 0xa33cfb0e0 | 0xa00000 |
| 337 | blk.37.attn_norm.weight | 0xa346fb0e0 | 0x5000 |
| 338 | blk.37.attn_output.weight | 0xa347000e0 | 0x2800000 |
| 339 | blk.37.attn_q.weight | 0xa36f000e0 | 0x2800000 |
| 340 | blk.37.attn_v.weight | 0xa397000e0 | 0xa00000 |
| 341 | blk.37.ffn_down.weight | 0xa3a1000e0 | 0x14000000 |
| 342 | blk.37.ffn_gate.weight | 0xa4e1000e0 | 0x14000000 |
| 343 | blk.37.ffn_norm.weight | 0xa621000e0 | 0x5000 |
| 344 | blk.37.ffn_up.weight | 0xa621050e0 | 0x14000000 |
Base Tensor Group : ~1B Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 0 | output.weight | Output (W) | (~671M) 671088640 | 5120 x 131072 x 1 x 1 | F16 | 16.0000 |
| 1 | output_norm.weight | Output Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 2 | token_embd.weight | Token Embedding (W) | (~671M) 671088640 | 5120 x 131072 x 1 x 1 | F16 | 16.0000 |
- Total elements in base: ( ~1B) 1342182400
- Percentage of total elements: 5.98%
- Bits per Weight (BPW) for base: 16.0001 bits
Block 0 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 3 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 4 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 5 | blk.0.attn_output.weight | Block 0 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 6 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 7 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 8 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 9 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 10 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 11 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.0: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.0: 16.0003 bits
Block 1 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 12 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 13 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 14 | blk.1.attn_output.weight | Block 1 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 15 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 16 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 17 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 18 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 19 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 20 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.1: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.1: 16.0003 bits
Block 2 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 21 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 22 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 23 | blk.2.attn_output.weight | Block 2 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 24 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 25 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 26 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 27 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 28 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 29 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.2: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.2: 16.0003 bits
Block 3 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 30 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 31 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 32 | blk.3.attn_output.weight | Block 3 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 33 | blk.3.attn_q.weight | Block 3 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 34 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 35 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 36 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 37 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 38 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.3: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.3: 16.0003 bits
Block 4 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 39 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 40 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 41 | blk.4.attn_output.weight | Block 4 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 42 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 43 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 44 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 45 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 46 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 47 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.4: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.4: 16.0003 bits
Block 5 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 48 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 49 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 50 | blk.5.attn_output.weight | Block 5 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 51 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 52 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 53 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 54 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 55 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 56 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.5: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.5: 16.0003 bits
Block 6 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 57 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 58 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 59 | blk.6.attn_output.weight | Block 6 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 60 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 61 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 62 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 63 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 64 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 65 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.6: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.6: 16.0003 bits
Block 7 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 66 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 67 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 68 | blk.7.attn_output.weight | Block 7 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 69 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 70 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 71 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 72 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 73 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 74 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.7: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.7: 16.0003 bits
Block 8 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 75 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 76 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 77 | blk.8.attn_output.weight | Block 8 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 78 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 79 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 80 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 81 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 82 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 83 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.8: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.8: 16.0003 bits
Block 9 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 84 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 85 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 86 | blk.9.attn_output.weight | Block 9 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 87 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 88 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 89 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 90 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 91 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 92 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.9: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.9: 16.0003 bits
Block 10 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 93 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 94 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 95 | blk.10.attn_output.weight | Block 10 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 96 | blk.10.attn_q.weight | Block 10 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 97 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 98 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 99 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 100 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 101 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.10: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.10: 16.0003 bits
Block 11 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 102 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 103 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 104 | blk.11.attn_output.weight | Block 11 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 105 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 106 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 107 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 108 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 109 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 110 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.11: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.11: 16.0003 bits
Block 12 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 111 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 112 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 113 | blk.12.attn_output.weight | Block 12 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 114 | blk.12.attn_q.weight | Block 12 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 115 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 116 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 117 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 118 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 119 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.12: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.12: 16.0003 bits
Block 13 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 120 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 121 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 122 | blk.13.attn_output.weight | Block 13 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 123 | blk.13.attn_q.weight | Block 13 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 124 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 125 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 126 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 127 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 128 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.13: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.13: 16.0003 bits
Block 14 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 129 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 130 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 131 | blk.14.attn_output.weight | Block 14 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 132 | blk.14.attn_q.weight | Block 14 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 133 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 134 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 135 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 136 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 137 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.14: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.14: 16.0003 bits
Block 15 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 138 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 139 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 140 | blk.15.attn_output.weight | Block 15 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 141 | blk.15.attn_q.weight | Block 15 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 142 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 143 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 144 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 145 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 146 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.15: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.15: 16.0003 bits
Block 16 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 147 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 148 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 149 | blk.16.attn_output.weight | Block 16 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 150 | blk.16.attn_q.weight | Block 16 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 151 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 152 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 153 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 154 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 155 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.16: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.16: 16.0003 bits
Block 17 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 156 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 157 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 158 | blk.17.attn_output.weight | Block 17 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 159 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 160 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 161 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 162 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 163 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 164 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.17: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.17: 16.0003 bits
Block 18 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 165 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 166 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 167 | blk.18.attn_output.weight | Block 18 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 168 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 169 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 170 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 171 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 172 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 173 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.18: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.18: 16.0003 bits
Block 19 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 174 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 175 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 176 | blk.19.attn_output.weight | Block 19 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 177 | blk.19.attn_q.weight | Block 19 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 178 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 179 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 180 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 181 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 182 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.19: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.19: 16.0003 bits
Block 20 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 183 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 184 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 185 | blk.20.attn_output.weight | Block 20 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 186 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 187 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 188 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 189 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 190 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 191 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.20: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.20: 16.0003 bits
Block 21 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 192 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 193 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 194 | blk.21.attn_output.weight | Block 21 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 195 | blk.21.attn_q.weight | Block 21 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 196 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 197 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 198 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 199 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 200 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.21: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.21: 16.0003 bits
Block 22 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 201 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 202 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 203 | blk.22.attn_output.weight | Block 22 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 204 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 205 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 206 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 207 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 208 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 209 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.22: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.22: 16.0003 bits
Block 23 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 210 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 211 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 212 | blk.23.attn_output.weight | Block 23 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 213 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 214 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 215 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 216 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 217 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 218 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.23: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.23: 16.0003 bits
Block 24 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 219 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 220 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 221 | blk.24.attn_output.weight | Block 24 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 222 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 223 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 224 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 225 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 226 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 227 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.24: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.24: 16.0003 bits
Block 25 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 228 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 229 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 230 | blk.25.attn_output.weight | Block 25 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 231 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 232 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 233 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 234 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 235 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 236 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.25: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.25: 16.0003 bits
Block 26 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 237 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 238 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 239 | blk.26.attn_output.weight | Block 26 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 240 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 241 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 242 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 243 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 244 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 245 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.26: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.26: 16.0003 bits
Block 27 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 246 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 247 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 248 | blk.27.attn_output.weight | Block 27 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 249 | blk.27.attn_q.weight | Block 27 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 250 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 251 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 252 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 253 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 254 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.27: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.27: 16.0003 bits
Block 28 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 255 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 256 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 257 | blk.28.attn_output.weight | Block 28 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 258 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 259 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 260 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 261 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 262 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 263 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.28: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.28: 16.0003 bits
Block 29 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 264 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 265 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 266 | blk.29.attn_output.weight | Block 29 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 267 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 268 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 269 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 270 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 271 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 272 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.29: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.29: 16.0003 bits
Block 30 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 273 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 274 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 275 | blk.30.attn_output.weight | Block 30 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 276 | blk.30.attn_q.weight | Block 30 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 277 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 278 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 279 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 280 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 281 | blk.30.ffn_up.weight | Block 30 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.30: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.30: 16.0003 bits
Block 31 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 282 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 283 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 284 | blk.31.attn_output.weight | Block 31 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 285 | blk.31.attn_q.weight | Block 31 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 286 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 287 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 288 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 289 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 290 | blk.31.ffn_up.weight | Block 31 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.31: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.31: 16.0003 bits
Block 32 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 291 | blk.32.attn_k.weight | Block 32 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 292 | blk.32.attn_norm.weight | Block 32 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 293 | blk.32.attn_output.weight | Block 32 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 294 | blk.32.attn_q.weight | Block 32 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 295 | blk.32.attn_v.weight | Block 32 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 296 | blk.32.ffn_down.weight | Block 32 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 297 | blk.32.ffn_gate.weight | Block 32 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 298 | blk.32.ffn_norm.weight | Block 32 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 299 | blk.32.ffn_up.weight | Block 32 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.32: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.32: 16.0003 bits
Block 33 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 300 | blk.33.attn_k.weight | Block 33 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 301 | blk.33.attn_norm.weight | Block 33 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 302 | blk.33.attn_output.weight | Block 33 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 303 | blk.33.attn_q.weight | Block 33 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 304 | blk.33.attn_v.weight | Block 33 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 305 | blk.33.ffn_down.weight | Block 33 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 306 | blk.33.ffn_gate.weight | Block 33 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 307 | blk.33.ffn_norm.weight | Block 33 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 308 | blk.33.ffn_up.weight | Block 33 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.33: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.33: 16.0003 bits
Block 34 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 309 | blk.34.attn_k.weight | Block 34 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 310 | blk.34.attn_norm.weight | Block 34 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 311 | blk.34.attn_output.weight | Block 34 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 312 | blk.34.attn_q.weight | Block 34 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 313 | blk.34.attn_v.weight | Block 34 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 314 | blk.34.ffn_down.weight | Block 34 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 315 | blk.34.ffn_gate.weight | Block 34 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 316 | blk.34.ffn_norm.weight | Block 34 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 317 | blk.34.ffn_up.weight | Block 34 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.34: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.34: 16.0003 bits
Block 35 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 318 | blk.35.attn_k.weight | Block 35 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 319 | blk.35.attn_norm.weight | Block 35 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 320 | blk.35.attn_output.weight | Block 35 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 321 | blk.35.attn_q.weight | Block 35 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 322 | blk.35.attn_v.weight | Block 35 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 323 | blk.35.ffn_down.weight | Block 35 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 324 | blk.35.ffn_gate.weight | Block 35 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 325 | blk.35.ffn_norm.weight | Block 35 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 326 | blk.35.ffn_up.weight | Block 35 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.35: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.35: 16.0003 bits
Block 36 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 327 | blk.36.attn_k.weight | Block 36 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 328 | blk.36.attn_norm.weight | Block 36 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 329 | blk.36.attn_output.weight | Block 36 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 330 | blk.36.attn_q.weight | Block 36 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 331 | blk.36.attn_v.weight | Block 36 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 332 | blk.36.ffn_down.weight | Block 36 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 333 | blk.36.ffn_gate.weight | Block 36 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 334 | blk.36.ffn_norm.weight | Block 36 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 335 | blk.36.ffn_up.weight | Block 36 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.36: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.36: 16.0003 bits
Block 37 Tensor Group : ~556M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | BPW |
|---|---|---|---|---|---|---|
| 336 | blk.37.attn_k.weight | Block 37 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 337 | blk.37.attn_norm.weight | Block 37 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 338 | blk.37.attn_output.weight | Block 37 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | 16.0000 |
| 339 | blk.37.attn_q.weight | Block 37 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | 16.0000 |
| 340 | blk.37.attn_v.weight | Block 37 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | 16.0000 |
| 341 | blk.37.ffn_down.weight | Block 37 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | 16.0000 |
| 342 | blk.37.ffn_gate.weight | Block 37 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
| 343 | blk.37.ffn_norm.weight | Block 37 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | 32.0000 |
| 344 | blk.37.ffn_up.weight | Block 37 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | 16.0000 |
- Total elements in blk.37: (~556M) 555755520
- Percentage of total elements: 2.47%
- Bits per Weight (BPW) for blk.37: 16.0003 bits
Total BPW for Mistral-Small-3.2-24B-Instruct-pruned-F16.gguf: 16.0003 bits