# Watt-Tool-8B-F16.gguf - GGUF Internal File Dump
- Endian: LITTLE endian
## Key Value Metadata Store
There are 39 key-value pairs in this file
| POS | TYPE | Count | Key | Value |
|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
| 1 | UINT32 | 1 | GGUF.version | 3 |
| 2 | UINT64 | 1 | GGUF.tensor_count | 292 |
| 3 | UINT64 | 1 | GGUF.kv_count | 36 |
| 4 | STRING | 1 | general.architecture | `llama` |
| 5 | STRING | 1 | general.type | `model` |
| 6 | STRING | 1 | general.name | `Watt Tool 8B GGUF` |
| 7 | STRING | 1 | general.finetune | `GGUF` |
| 8 | STRING | 1 | general.basename | `Watt-Tool` |
| 9 | STRING | 1 | general.size_label | `8B` |
| 10 | STRING | 1 | general.license | `apache-2.0` |
| 11 | UINT32 | 1 | general.base_model.count | 1 |
| 12 | STRING | 1 | general.base_model.0.name | `Llama 3.1 8B Instruct` |
| 13 | STRING | 1 | general.base_model.0.organization | `Meta Llama` |
| 14 | STRING | 1 | general.base_model.0.repo_url | `https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct` |
| 15 | [STRING] | 4 | general.tags | [ `function-calling`, `tool-use`, `llama`, `bfcl` ] |
| 16 | [STRING] | 1 | general.languages | [ `en` ] |
| 17 | UINT32 | 1 | llama.block_count | 32 |
| 18 | UINT32 | 1 | llama.context_length | 131072 |
| 19 | UINT32 | 1 | llama.embedding_length | 4096 |
| 20 | UINT32 | 1 | llama.feed_forward_length | 14336 |
| 21 | UINT32 | 1 | llama.attention.head_count | 32 |
| 22 | UINT32 | 1 | llama.attention.head_count_kv | 8 |
| 23 | FLOAT32 | 1 | llama.rope.freq_base | 500000.0 |
| 24 | FLOAT32 | 1 | llama.attention.layer_norm_rms_epsilon | 1e-05 |
| 25 | UINT32 | 1 | llama.attention.key_length | 128 |
| 26 | UINT32 | 1 | llama.attention.value_length | 128 |
| 27 | UINT32 | 1 | general.file_type | 1 |
| 28 | UINT32 | 1 | llama.vocab_size | 128256 |
| 29 | UINT32 | 1 | llama.rope.dimension_count | 128 |
| 30 | STRING | 1 | tokenizer.ggml.model | `gpt2` |
| 31 | STRING | 1 | tokenizer.ggml.pre | `llama-bpe` |
| 32 | [STRING] | 128256 | tokenizer.ggml.tokens | [ `!`, `"`, `#`, `$`, `%`, ... ] |
| 33 | [INT32] | 128256 | tokenizer.ggml.token_type | [ 1, 1, 1, 1, 1, 1, 1, ... ] |
| 34 | [STRING] | 280147 | tokenizer.ggml.merges | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ] |
| 35 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 128000 |
| 36 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 128009 |
| 37 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 128009 |
| 38 | STRING | 1 | tokenizer.chat_template | `{{ '<|begin_of_text|>' }}{% if`...`d|>' }}{% endif %}{% endfor %}` |
| 39 | UINT32 | 1 | general.quantization_version | 2 |
## Tensors Overview ~8B Elements
Total number of elements in all tensors: 8030261312 Elements
- [Watt-Tool-8B-F16.gguf - GGUF Internal File Dump](#watt-tool-8b-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 : ~218M Elements](#block-0-tensor-group--218m-elements)
- [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
- [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
- [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
- [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
- [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
- [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
- [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
- [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
- [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
- [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
- [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
- [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
- [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
- [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
- [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
- [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
- [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
- [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
- [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
- [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
- [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
- [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
- [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
- [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
- [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
- [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
- [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
- [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
- [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
- [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
- [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-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 | rope_freqs.weight | 0x779520 | 0x100 |
| 1 | output.weight | 0x779620 | 0x3ea00000 |
| 2 | token_embd.weight | 0x3f179620 | 0x3ea00000 |
| 3 | blk.0.attn_norm.weight | 0x7db79620 | 0x4000 |
| 4 | blk.0.ffn_down.weight | 0x7db7d620 | 0x7000000 |
| 5 | blk.0.ffn_gate.weight | 0x84b7d620 | 0x7000000 |
| 6 | blk.0.ffn_up.weight | 0x8bb7d620 | 0x7000000 |
| 7 | blk.0.ffn_norm.weight | 0x92b7d620 | 0x4000 |
| 8 | blk.0.attn_k.weight | 0x92b81620 | 0x800000 |
| 9 | blk.0.attn_output.weight | 0x93381620 | 0x2000000 |
| 10 | blk.0.attn_q.weight | 0x95381620 | 0x2000000 |
| 11 | blk.0.attn_v.weight | 0x97381620 | 0x800000 |
| 12 | blk.1.attn_norm.weight | 0x97b81620 | 0x4000 |
| 13 | blk.1.ffn_down.weight | 0x97b85620 | 0x7000000 |
| 14 | blk.1.ffn_gate.weight | 0x9eb85620 | 0x7000000 |
| 15 | blk.1.ffn_up.weight | 0xa5b85620 | 0x7000000 |
| 16 | blk.1.ffn_norm.weight | 0xacb85620 | 0x4000 |
| 17 | blk.1.attn_k.weight | 0xacb89620 | 0x800000 |
| 18 | blk.1.attn_output.weight | 0xad389620 | 0x2000000 |
| 19 | blk.1.attn_q.weight | 0xaf389620 | 0x2000000 |
| 20 | blk.1.attn_v.weight | 0xb1389620 | 0x800000 |
| 21 | blk.10.attn_norm.weight | 0xb1b89620 | 0x4000 |
| 22 | blk.10.ffn_down.weight | 0xb1b8d620 | 0x7000000 |
| 23 | blk.10.ffn_gate.weight | 0xb8b8d620 | 0x7000000 |
| 24 | blk.10.ffn_up.weight | 0xbfb8d620 | 0x7000000 |
| 25 | blk.10.ffn_norm.weight | 0xc6b8d620 | 0x4000 |
| 26 | blk.10.attn_k.weight | 0xc6b91620 | 0x800000 |
| 27 | blk.10.attn_output.weight | 0xc7391620 | 0x2000000 |
| 28 | blk.10.attn_q.weight | 0xc9391620 | 0x2000000 |
| 29 | blk.10.attn_v.weight | 0xcb391620 | 0x800000 |
| 30 | blk.11.attn_norm.weight | 0xcbb91620 | 0x4000 |
| 31 | blk.11.ffn_down.weight | 0xcbb95620 | 0x7000000 |
| 32 | blk.11.ffn_gate.weight | 0xd2b95620 | 0x7000000 |
| 33 | blk.11.ffn_up.weight | 0xd9b95620 | 0x7000000 |
| 34 | blk.11.ffn_norm.weight | 0xe0b95620 | 0x4000 |
| 35 | blk.11.attn_k.weight | 0xe0b99620 | 0x800000 |
| 36 | blk.11.attn_output.weight | 0xe1399620 | 0x2000000 |
| 37 | blk.11.attn_q.weight | 0xe3399620 | 0x2000000 |
| 38 | blk.11.attn_v.weight | 0xe5399620 | 0x800000 |
| 39 | blk.12.attn_norm.weight | 0xe5b99620 | 0x4000 |
| 40 | blk.12.ffn_down.weight | 0xe5b9d620 | 0x7000000 |
| 41 | blk.12.ffn_gate.weight | 0xecb9d620 | 0x7000000 |
| 42 | blk.12.ffn_up.weight | 0xf3b9d620 | 0x7000000 |
| 43 | blk.12.ffn_norm.weight | 0xfab9d620 | 0x4000 |
| 44 | blk.12.attn_k.weight | 0xfaba1620 | 0x800000 |
| 45 | blk.12.attn_output.weight | 0xfb3a1620 | 0x2000000 |
| 46 | blk.12.attn_q.weight | 0xfd3a1620 | 0x2000000 |
| 47 | blk.12.attn_v.weight | 0xff3a1620 | 0x800000 |
| 48 | blk.13.attn_norm.weight | 0xffba1620 | 0x4000 |
| 49 | blk.13.ffn_down.weight | 0xffba5620 | 0x7000000 |
| 50 | blk.13.ffn_gate.weight | 0x106ba5620 | 0x7000000 |
| 51 | blk.13.ffn_up.weight | 0x10dba5620 | 0x7000000 |
| 52 | blk.13.ffn_norm.weight | 0x114ba5620 | 0x4000 |
| 53 | blk.13.attn_k.weight | 0x114ba9620 | 0x800000 |
| 54 | blk.13.attn_output.weight | 0x1153a9620 | 0x2000000 |
| 55 | blk.13.attn_q.weight | 0x1173a9620 | 0x2000000 |
| 56 | blk.13.attn_v.weight | 0x1193a9620 | 0x800000 |
| 57 | blk.14.attn_norm.weight | 0x119ba9620 | 0x4000 |
| 58 | blk.14.ffn_down.weight | 0x119bad620 | 0x7000000 |
| 59 | blk.14.ffn_gate.weight | 0x120bad620 | 0x7000000 |
| 60 | blk.14.ffn_up.weight | 0x127bad620 | 0x7000000 |
| 61 | blk.14.ffn_norm.weight | 0x12ebad620 | 0x4000 |
| 62 | blk.14.attn_k.weight | 0x12ebb1620 | 0x800000 |
| 63 | blk.14.attn_output.weight | 0x12f3b1620 | 0x2000000 |
| 64 | blk.14.attn_q.weight | 0x1313b1620 | 0x2000000 |
| 65 | blk.14.attn_v.weight | 0x1333b1620 | 0x800000 |
| 66 | blk.15.attn_norm.weight | 0x133bb1620 | 0x4000 |
| 67 | blk.15.ffn_down.weight | 0x133bb5620 | 0x7000000 |
| 68 | blk.15.ffn_gate.weight | 0x13abb5620 | 0x7000000 |
| 69 | blk.15.ffn_up.weight | 0x141bb5620 | 0x7000000 |
| 70 | blk.15.ffn_norm.weight | 0x148bb5620 | 0x4000 |
| 71 | blk.15.attn_k.weight | 0x148bb9620 | 0x800000 |
| 72 | blk.15.attn_output.weight | 0x1493b9620 | 0x2000000 |
| 73 | blk.15.attn_q.weight | 0x14b3b9620 | 0x2000000 |
| 74 | blk.15.attn_v.weight | 0x14d3b9620 | 0x800000 |
| 75 | blk.16.attn_norm.weight | 0x14dbb9620 | 0x4000 |
| 76 | blk.16.ffn_down.weight | 0x14dbbd620 | 0x7000000 |
| 77 | blk.16.ffn_gate.weight | 0x154bbd620 | 0x7000000 |
| 78 | blk.16.ffn_up.weight | 0x15bbbd620 | 0x7000000 |
| 79 | blk.16.ffn_norm.weight | 0x162bbd620 | 0x4000 |
| 80 | blk.16.attn_k.weight | 0x162bc1620 | 0x800000 |
| 81 | blk.16.attn_output.weight | 0x1633c1620 | 0x2000000 |
| 82 | blk.16.attn_q.weight | 0x1653c1620 | 0x2000000 |
| 83 | blk.16.attn_v.weight | 0x1673c1620 | 0x800000 |
| 84 | blk.17.attn_norm.weight | 0x167bc1620 | 0x4000 |
| 85 | blk.17.ffn_down.weight | 0x167bc5620 | 0x7000000 |
| 86 | blk.17.ffn_gate.weight | 0x16ebc5620 | 0x7000000 |
| 87 | blk.17.ffn_up.weight | 0x175bc5620 | 0x7000000 |
| 88 | blk.17.ffn_norm.weight | 0x17cbc5620 | 0x4000 |
| 89 | blk.17.attn_k.weight | 0x17cbc9620 | 0x800000 |
| 90 | blk.17.attn_output.weight | 0x17d3c9620 | 0x2000000 |
| 91 | blk.17.attn_q.weight | 0x17f3c9620 | 0x2000000 |
| 92 | blk.17.attn_v.weight | 0x1813c9620 | 0x800000 |
| 93 | blk.18.attn_norm.weight | 0x181bc9620 | 0x4000 |
| 94 | blk.18.ffn_down.weight | 0x181bcd620 | 0x7000000 |
| 95 | blk.18.ffn_gate.weight | 0x188bcd620 | 0x7000000 |
| 96 | blk.18.ffn_up.weight | 0x18fbcd620 | 0x7000000 |
| 97 | blk.18.ffn_norm.weight | 0x196bcd620 | 0x4000 |
| 98 | blk.18.attn_k.weight | 0x196bd1620 | 0x800000 |
| 99 | blk.18.attn_output.weight | 0x1973d1620 | 0x2000000 |
| 100 | blk.18.attn_q.weight | 0x1993d1620 | 0x2000000 |
| 101 | blk.18.attn_v.weight | 0x19b3d1620 | 0x800000 |
| 102 | blk.19.attn_norm.weight | 0x19bbd1620 | 0x4000 |
| 103 | blk.19.ffn_down.weight | 0x19bbd5620 | 0x7000000 |
| 104 | blk.19.ffn_gate.weight | 0x1a2bd5620 | 0x7000000 |
| 105 | blk.19.ffn_up.weight | 0x1a9bd5620 | 0x7000000 |
| 106 | blk.19.ffn_norm.weight | 0x1b0bd5620 | 0x4000 |
| 107 | blk.19.attn_k.weight | 0x1b0bd9620 | 0x800000 |
| 108 | blk.19.attn_output.weight | 0x1b13d9620 | 0x2000000 |
| 109 | blk.19.attn_q.weight | 0x1b33d9620 | 0x2000000 |
| 110 | blk.19.attn_v.weight | 0x1b53d9620 | 0x800000 |
| 111 | blk.2.attn_norm.weight | 0x1b5bd9620 | 0x4000 |
| 112 | blk.2.ffn_down.weight | 0x1b5bdd620 | 0x7000000 |
| 113 | blk.2.ffn_gate.weight | 0x1bcbdd620 | 0x7000000 |
| 114 | blk.2.ffn_up.weight | 0x1c3bdd620 | 0x7000000 |
| 115 | blk.2.ffn_norm.weight | 0x1cabdd620 | 0x4000 |
| 116 | blk.2.attn_k.weight | 0x1cabe1620 | 0x800000 |
| 117 | blk.2.attn_output.weight | 0x1cb3e1620 | 0x2000000 |
| 118 | blk.2.attn_q.weight | 0x1cd3e1620 | 0x2000000 |
| 119 | blk.2.attn_v.weight | 0x1cf3e1620 | 0x800000 |
| 120 | blk.20.attn_norm.weight | 0x1cfbe1620 | 0x4000 |
| 121 | blk.20.ffn_down.weight | 0x1cfbe5620 | 0x7000000 |
| 122 | blk.20.ffn_gate.weight | 0x1d6be5620 | 0x7000000 |
| 123 | blk.20.ffn_up.weight | 0x1ddbe5620 | 0x7000000 |
| 124 | blk.20.ffn_norm.weight | 0x1e4be5620 | 0x4000 |
| 125 | blk.20.attn_k.weight | 0x1e4be9620 | 0x800000 |
| 126 | blk.20.attn_output.weight | 0x1e53e9620 | 0x2000000 |
| 127 | blk.20.attn_q.weight | 0x1e73e9620 | 0x2000000 |
| 128 | blk.20.attn_v.weight | 0x1e93e9620 | 0x800000 |
| 129 | blk.21.attn_norm.weight | 0x1e9be9620 | 0x4000 |
| 130 | blk.21.ffn_down.weight | 0x1e9bed620 | 0x7000000 |
| 131 | blk.21.ffn_gate.weight | 0x1f0bed620 | 0x7000000 |
| 132 | blk.21.ffn_up.weight | 0x1f7bed620 | 0x7000000 |
| 133 | blk.21.ffn_norm.weight | 0x1febed620 | 0x4000 |
| 134 | blk.21.attn_k.weight | 0x1febf1620 | 0x800000 |
| 135 | blk.21.attn_output.weight | 0x1ff3f1620 | 0x2000000 |
| 136 | blk.21.attn_q.weight | 0x2013f1620 | 0x2000000 |
| 137 | blk.21.attn_v.weight | 0x2033f1620 | 0x800000 |
| 138 | blk.22.attn_norm.weight | 0x203bf1620 | 0x4000 |
| 139 | blk.22.ffn_down.weight | 0x203bf5620 | 0x7000000 |
| 140 | blk.22.ffn_gate.weight | 0x20abf5620 | 0x7000000 |
| 141 | blk.22.ffn_up.weight | 0x211bf5620 | 0x7000000 |
| 142 | blk.22.ffn_norm.weight | 0x218bf5620 | 0x4000 |
| 143 | blk.22.attn_k.weight | 0x218bf9620 | 0x800000 |
| 144 | blk.22.attn_output.weight | 0x2193f9620 | 0x2000000 |
| 145 | blk.22.attn_q.weight | 0x21b3f9620 | 0x2000000 |
| 146 | blk.22.attn_v.weight | 0x21d3f9620 | 0x800000 |
| 147 | blk.23.attn_norm.weight | 0x21dbf9620 | 0x4000 |
| 148 | blk.23.ffn_down.weight | 0x21dbfd620 | 0x7000000 |
| 149 | blk.23.ffn_gate.weight | 0x224bfd620 | 0x7000000 |
| 150 | blk.23.ffn_up.weight | 0x22bbfd620 | 0x7000000 |
| 151 | blk.23.ffn_norm.weight | 0x232bfd620 | 0x4000 |
| 152 | blk.23.attn_k.weight | 0x232c01620 | 0x800000 |
| 153 | blk.23.attn_output.weight | 0x233401620 | 0x2000000 |
| 154 | blk.23.attn_q.weight | 0x235401620 | 0x2000000 |
| 155 | blk.23.attn_v.weight | 0x237401620 | 0x800000 |
| 156 | blk.24.attn_norm.weight | 0x237c01620 | 0x4000 |
| 157 | blk.24.ffn_down.weight | 0x237c05620 | 0x7000000 |
| 158 | blk.24.ffn_gate.weight | 0x23ec05620 | 0x7000000 |
| 159 | blk.24.ffn_up.weight | 0x245c05620 | 0x7000000 |
| 160 | blk.24.ffn_norm.weight | 0x24cc05620 | 0x4000 |
| 161 | blk.24.attn_k.weight | 0x24cc09620 | 0x800000 |
| 162 | blk.24.attn_output.weight | 0x24d409620 | 0x2000000 |
| 163 | blk.24.attn_q.weight | 0x24f409620 | 0x2000000 |
| 164 | blk.24.attn_v.weight | 0x251409620 | 0x800000 |
| 165 | blk.25.attn_norm.weight | 0x251c09620 | 0x4000 |
| 166 | blk.25.ffn_down.weight | 0x251c0d620 | 0x7000000 |
| 167 | blk.25.ffn_gate.weight | 0x258c0d620 | 0x7000000 |
| 168 | blk.25.ffn_up.weight | 0x25fc0d620 | 0x7000000 |
| 169 | blk.25.ffn_norm.weight | 0x266c0d620 | 0x4000 |
| 170 | blk.25.attn_k.weight | 0x266c11620 | 0x800000 |
| 171 | blk.25.attn_output.weight | 0x267411620 | 0x2000000 |
| 172 | blk.25.attn_q.weight | 0x269411620 | 0x2000000 |
| 173 | blk.25.attn_v.weight | 0x26b411620 | 0x800000 |
| 174 | blk.26.attn_norm.weight | 0x26bc11620 | 0x4000 |
| 175 | blk.26.ffn_down.weight | 0x26bc15620 | 0x7000000 |
| 176 | blk.26.ffn_gate.weight | 0x272c15620 | 0x7000000 |
| 177 | blk.26.ffn_up.weight | 0x279c15620 | 0x7000000 |
| 178 | blk.26.ffn_norm.weight | 0x280c15620 | 0x4000 |
| 179 | blk.26.attn_k.weight | 0x280c19620 | 0x800000 |
| 180 | blk.26.attn_output.weight | 0x281419620 | 0x2000000 |
| 181 | blk.26.attn_q.weight | 0x283419620 | 0x2000000 |
| 182 | blk.26.attn_v.weight | 0x285419620 | 0x800000 |
| 183 | blk.27.attn_norm.weight | 0x285c19620 | 0x4000 |
| 184 | blk.27.ffn_down.weight | 0x285c1d620 | 0x7000000 |
| 185 | blk.27.ffn_gate.weight | 0x28cc1d620 | 0x7000000 |
| 186 | blk.27.ffn_up.weight | 0x293c1d620 | 0x7000000 |
| 187 | blk.27.ffn_norm.weight | 0x29ac1d620 | 0x4000 |
| 188 | blk.27.attn_k.weight | 0x29ac21620 | 0x800000 |
| 189 | blk.27.attn_output.weight | 0x29b421620 | 0x2000000 |
| 190 | blk.27.attn_q.weight | 0x29d421620 | 0x2000000 |
| 191 | blk.27.attn_v.weight | 0x29f421620 | 0x800000 |
| 192 | blk.28.attn_norm.weight | 0x29fc21620 | 0x4000 |
| 193 | blk.28.ffn_down.weight | 0x29fc25620 | 0x7000000 |
| 194 | blk.28.ffn_gate.weight | 0x2a6c25620 | 0x7000000 |
| 195 | blk.28.ffn_up.weight | 0x2adc25620 | 0x7000000 |
| 196 | blk.28.ffn_norm.weight | 0x2b4c25620 | 0x4000 |
| 197 | blk.28.attn_k.weight | 0x2b4c29620 | 0x800000 |
| 198 | blk.28.attn_output.weight | 0x2b5429620 | 0x2000000 |
| 199 | blk.28.attn_q.weight | 0x2b7429620 | 0x2000000 |
| 200 | blk.28.attn_v.weight | 0x2b9429620 | 0x800000 |
| 201 | blk.29.attn_norm.weight | 0x2b9c29620 | 0x4000 |
| 202 | blk.29.ffn_down.weight | 0x2b9c2d620 | 0x7000000 |
| 203 | blk.29.ffn_gate.weight | 0x2c0c2d620 | 0x7000000 |
| 204 | blk.29.ffn_up.weight | 0x2c7c2d620 | 0x7000000 |
| 205 | blk.29.ffn_norm.weight | 0x2cec2d620 | 0x4000 |
| 206 | blk.29.attn_k.weight | 0x2cec31620 | 0x800000 |
| 207 | blk.29.attn_output.weight | 0x2cf431620 | 0x2000000 |
| 208 | blk.29.attn_q.weight | 0x2d1431620 | 0x2000000 |
| 209 | blk.29.attn_v.weight | 0x2d3431620 | 0x800000 |
| 210 | blk.3.attn_norm.weight | 0x2d3c31620 | 0x4000 |
| 211 | blk.3.ffn_down.weight | 0x2d3c35620 | 0x7000000 |
| 212 | blk.3.ffn_gate.weight | 0x2dac35620 | 0x7000000 |
| 213 | blk.3.ffn_up.weight | 0x2e1c35620 | 0x7000000 |
| 214 | blk.3.ffn_norm.weight | 0x2e8c35620 | 0x4000 |
| 215 | blk.3.attn_k.weight | 0x2e8c39620 | 0x800000 |
| 216 | blk.3.attn_output.weight | 0x2e9439620 | 0x2000000 |
| 217 | blk.3.attn_q.weight | 0x2eb439620 | 0x2000000 |
| 218 | blk.3.attn_v.weight | 0x2ed439620 | 0x800000 |
| 219 | blk.30.attn_norm.weight | 0x2edc39620 | 0x4000 |
| 220 | blk.30.ffn_down.weight | 0x2edc3d620 | 0x7000000 |
| 221 | blk.30.ffn_gate.weight | 0x2f4c3d620 | 0x7000000 |
| 222 | blk.30.ffn_up.weight | 0x2fbc3d620 | 0x7000000 |
| 223 | blk.30.ffn_norm.weight | 0x302c3d620 | 0x4000 |
| 224 | blk.30.attn_k.weight | 0x302c41620 | 0x800000 |
| 225 | blk.30.attn_output.weight | 0x303441620 | 0x2000000 |
| 226 | blk.30.attn_q.weight | 0x305441620 | 0x2000000 |
| 227 | blk.30.attn_v.weight | 0x307441620 | 0x800000 |
| 228 | blk.31.attn_norm.weight | 0x307c41620 | 0x4000 |
| 229 | blk.31.ffn_down.weight | 0x307c45620 | 0x7000000 |
| 230 | blk.31.ffn_gate.weight | 0x30ec45620 | 0x7000000 |
| 231 | blk.31.ffn_up.weight | 0x315c45620 | 0x7000000 |
| 232 | blk.31.ffn_norm.weight | 0x31cc45620 | 0x4000 |
| 233 | blk.31.attn_k.weight | 0x31cc49620 | 0x800000 |
| 234 | blk.31.attn_output.weight | 0x31d449620 | 0x2000000 |
| 235 | blk.31.attn_q.weight | 0x31f449620 | 0x2000000 |
| 236 | blk.31.attn_v.weight | 0x321449620 | 0x800000 |
| 237 | blk.4.attn_norm.weight | 0x321c49620 | 0x4000 |
| 238 | blk.4.ffn_down.weight | 0x321c4d620 | 0x7000000 |
| 239 | blk.4.ffn_gate.weight | 0x328c4d620 | 0x7000000 |
| 240 | blk.4.ffn_up.weight | 0x32fc4d620 | 0x7000000 |
| 241 | blk.4.ffn_norm.weight | 0x336c4d620 | 0x4000 |
| 242 | blk.4.attn_k.weight | 0x336c51620 | 0x800000 |
| 243 | blk.4.attn_output.weight | 0x337451620 | 0x2000000 |
| 244 | blk.4.attn_q.weight | 0x339451620 | 0x2000000 |
| 245 | blk.4.attn_v.weight | 0x33b451620 | 0x800000 |
| 246 | blk.5.attn_norm.weight | 0x33bc51620 | 0x4000 |
| 247 | blk.5.ffn_down.weight | 0x33bc55620 | 0x7000000 |
| 248 | blk.5.ffn_gate.weight | 0x342c55620 | 0x7000000 |
| 249 | blk.5.ffn_up.weight | 0x349c55620 | 0x7000000 |
| 250 | blk.5.ffn_norm.weight | 0x350c55620 | 0x4000 |
| 251 | blk.5.attn_k.weight | 0x350c59620 | 0x800000 |
| 252 | blk.5.attn_output.weight | 0x351459620 | 0x2000000 |
| 253 | blk.5.attn_q.weight | 0x353459620 | 0x2000000 |
| 254 | blk.5.attn_v.weight | 0x355459620 | 0x800000 |
| 255 | blk.6.attn_norm.weight | 0x355c59620 | 0x4000 |
| 256 | blk.6.ffn_down.weight | 0x355c5d620 | 0x7000000 |
| 257 | blk.6.ffn_gate.weight | 0x35cc5d620 | 0x7000000 |
| 258 | blk.6.ffn_up.weight | 0x363c5d620 | 0x7000000 |
| 259 | blk.6.ffn_norm.weight | 0x36ac5d620 | 0x4000 |
| 260 | blk.6.attn_k.weight | 0x36ac61620 | 0x800000 |
| 261 | blk.6.attn_output.weight | 0x36b461620 | 0x2000000 |
| 262 | blk.6.attn_q.weight | 0x36d461620 | 0x2000000 |
| 263 | blk.6.attn_v.weight | 0x36f461620 | 0x800000 |
| 264 | blk.7.attn_norm.weight | 0x36fc61620 | 0x4000 |
| 265 | blk.7.ffn_down.weight | 0x36fc65620 | 0x7000000 |
| 266 | blk.7.ffn_gate.weight | 0x376c65620 | 0x7000000 |
| 267 | blk.7.ffn_up.weight | 0x37dc65620 | 0x7000000 |
| 268 | blk.7.ffn_norm.weight | 0x384c65620 | 0x4000 |
| 269 | blk.7.attn_k.weight | 0x384c69620 | 0x800000 |
| 270 | blk.7.attn_output.weight | 0x385469620 | 0x2000000 |
| 271 | blk.7.attn_q.weight | 0x387469620 | 0x2000000 |
| 272 | blk.7.attn_v.weight | 0x389469620 | 0x800000 |
| 273 | blk.8.attn_norm.weight | 0x389c69620 | 0x4000 |
| 274 | blk.8.ffn_down.weight | 0x389c6d620 | 0x7000000 |
| 275 | blk.8.ffn_gate.weight | 0x390c6d620 | 0x7000000 |
| 276 | blk.8.ffn_up.weight | 0x397c6d620 | 0x7000000 |
| 277 | blk.8.ffn_norm.weight | 0x39ec6d620 | 0x4000 |
| 278 | blk.8.attn_k.weight | 0x39ec71620 | 0x800000 |
| 279 | blk.8.attn_output.weight | 0x39f471620 | 0x2000000 |
| 280 | blk.8.attn_q.weight | 0x3a1471620 | 0x2000000 |
| 281 | blk.8.attn_v.weight | 0x3a3471620 | 0x800000 |
| 282 | blk.9.attn_norm.weight | 0x3a3c71620 | 0x4000 |
| 283 | blk.9.ffn_down.weight | 0x3a3c75620 | 0x7000000 |
| 284 | blk.9.ffn_gate.weight | 0x3aac75620 | 0x7000000 |
| 285 | blk.9.ffn_up.weight | 0x3b1c75620 | 0x7000000 |
| 286 | blk.9.ffn_norm.weight | 0x3b8c75620 | 0x4000 |
| 287 | blk.9.attn_k.weight | 0x3b8c79620 | 0x800000 |
| 288 | blk.9.attn_output.weight | 0x3b9479620 | 0x2000000 |
| 289 | blk.9.attn_q.weight | 0x3bb479620 | 0x2000000 |
| 290 | blk.9.attn_v.weight | 0x3bd479620 | 0x800000 |
| 291 | output_norm.weight | 0x3bdc79620 | 0x4000 |
### Base Tensor Group : ~1B Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
| 0 | rope_freqs.weight | Rope_Freqs (W) | ( 64) 64 | 64 x 1 x 1 x 1 | F32 |
| 1 | output.weight | Output (W) | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | F16 |
| 2 | token_embd.weight | Token Embedding (W) | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | F16 |
| 291 | output_norm.weight | Output Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
- Total elements in base: ( ~1B) 1050677312
- Percentage of total elements: 13.08%
### Block 0 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 3 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 4 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 5 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 6 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 7 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 8 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 9 | blk.0.attn_output.weight | Block 0 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 10 | blk.0.attn_q.weight | Block 0 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 11 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.0: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 1 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 12 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 13 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 14 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 15 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 16 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 17 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 18 | blk.1.attn_output.weight | Block 1 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 19 | blk.1.attn_q.weight | Block 1 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 20 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.1: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 10 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 21 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 22 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 23 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 24 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 25 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 26 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 27 | blk.10.attn_output.weight | Block 10 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 28 | blk.10.attn_q.weight | Block 10 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 29 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.10: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 11 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 30 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 31 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 32 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 33 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 34 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 35 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 36 | blk.11.attn_output.weight | Block 11 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 37 | blk.11.attn_q.weight | Block 11 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 38 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.11: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 12 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 39 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 40 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 41 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 42 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 43 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 44 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 45 | blk.12.attn_output.weight | Block 12 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 46 | blk.12.attn_q.weight | Block 12 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 47 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.12: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 13 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 48 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 49 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 50 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 51 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 52 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 53 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 54 | blk.13.attn_output.weight | Block 13 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 55 | blk.13.attn_q.weight | Block 13 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 56 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.13: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 14 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 57 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 58 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 59 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 60 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 61 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 62 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 63 | blk.14.attn_output.weight | Block 14 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 64 | blk.14.attn_q.weight | Block 14 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 65 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.14: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 15 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 66 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 67 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 68 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 69 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 70 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 71 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 72 | blk.15.attn_output.weight | Block 15 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 73 | blk.15.attn_q.weight | Block 15 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 74 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.15: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 16 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 75 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 76 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 77 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 78 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 79 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 80 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 81 | blk.16.attn_output.weight | Block 16 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 82 | blk.16.attn_q.weight | Block 16 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 83 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.16: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 17 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 84 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 85 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 86 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 87 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 88 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 89 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 90 | blk.17.attn_output.weight | Block 17 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 91 | blk.17.attn_q.weight | Block 17 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 92 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.17: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 18 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 93 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 94 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 95 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 96 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 97 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 98 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 99 | blk.18.attn_output.weight | Block 18 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 100 | blk.18.attn_q.weight | Block 18 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 101 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.18: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 19 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 102 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 103 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 104 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 105 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 106 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 107 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 108 | blk.19.attn_output.weight | Block 19 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 109 | blk.19.attn_q.weight | Block 19 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 110 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.19: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 2 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 111 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 112 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 113 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 114 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 115 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 116 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 117 | blk.2.attn_output.weight | Block 2 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 118 | blk.2.attn_q.weight | Block 2 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 119 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.2: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 20 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 120 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 121 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 122 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 123 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 124 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 125 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 126 | blk.20.attn_output.weight | Block 20 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 127 | blk.20.attn_q.weight | Block 20 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 128 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.20: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 21 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 129 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 130 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 131 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 132 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 133 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 134 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 135 | blk.21.attn_output.weight | Block 21 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 136 | blk.21.attn_q.weight | Block 21 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 137 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.21: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 22 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 138 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 139 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 140 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 141 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 142 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 143 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 144 | blk.22.attn_output.weight | Block 22 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 145 | blk.22.attn_q.weight | Block 22 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 146 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.22: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 23 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 147 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 148 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 149 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 150 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 151 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 152 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 153 | blk.23.attn_output.weight | Block 23 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 154 | blk.23.attn_q.weight | Block 23 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 155 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.23: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 24 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 156 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 157 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 158 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 159 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 160 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 161 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 162 | blk.24.attn_output.weight | Block 24 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 163 | blk.24.attn_q.weight | Block 24 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 164 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.24: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 25 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 165 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 166 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 167 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 168 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 169 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 170 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 171 | blk.25.attn_output.weight | Block 25 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 172 | blk.25.attn_q.weight | Block 25 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 173 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.25: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 26 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 174 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 175 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 176 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 177 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 178 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 179 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 180 | blk.26.attn_output.weight | Block 26 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 181 | blk.26.attn_q.weight | Block 26 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 182 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.26: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 27 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 183 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 184 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 185 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 186 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 187 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 188 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 189 | blk.27.attn_output.weight | Block 27 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 190 | blk.27.attn_q.weight | Block 27 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 191 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.27: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 28 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 192 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 193 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 194 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 195 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 196 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 197 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 198 | blk.28.attn_output.weight | Block 28 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 199 | blk.28.attn_q.weight | Block 28 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 200 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.28: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 29 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 201 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 202 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 203 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 204 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 205 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 206 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 207 | blk.29.attn_output.weight | Block 29 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 208 | blk.29.attn_q.weight | Block 29 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 209 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.29: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 3 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 210 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 211 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 212 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 213 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 214 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 215 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 216 | blk.3.attn_output.weight | Block 3 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 217 | blk.3.attn_q.weight | Block 3 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 218 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.3: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 30 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 219 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 220 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 221 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 222 | blk.30.ffn_up.weight | Block 30 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 223 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 224 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 225 | blk.30.attn_output.weight | Block 30 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 226 | blk.30.attn_q.weight | Block 30 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 227 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.30: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 31 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
| 228 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 229 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 230 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 231 | blk.31.ffn_up.weight | Block 31 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 232 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 233 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 234 | blk.31.attn_output.weight | Block 31 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 235 | blk.31.attn_q.weight | Block 31 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 236 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.31: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 4 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 237 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 238 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 239 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 240 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 241 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 242 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 243 | blk.4.attn_output.weight | Block 4 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 244 | blk.4.attn_q.weight | Block 4 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 245 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.4: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 5 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 246 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 247 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 248 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 249 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 250 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 251 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 252 | blk.5.attn_output.weight | Block 5 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 253 | blk.5.attn_q.weight | Block 5 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 254 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.5: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 6 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 255 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 256 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 257 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 258 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 259 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 260 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 261 | blk.6.attn_output.weight | Block 6 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 262 | blk.6.attn_q.weight | Block 6 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 263 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.6: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 7 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 264 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 265 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 266 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 267 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 268 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 269 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 270 | blk.7.attn_output.weight | Block 7 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 271 | blk.7.attn_q.weight | Block 7 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 272 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.7: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 8 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 273 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 274 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 275 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 276 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 277 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 278 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 279 | blk.8.attn_output.weight | Block 8 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 280 | blk.8.attn_q.weight | Block 8 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 281 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.8: (~218M) 218112000
- Percentage of total elements: 2.72%
### Block 9 Tensor Group : ~218M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
| 282 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 283 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | F16 |
| 284 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 285 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | F16 |
| 286 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 287 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
| 288 | blk.9.attn_output.weight | Block 9 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 289 | blk.9.attn_q.weight | Block 9 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | F16 |
| 290 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | F16 |
- Total elements in blk.9: (~218M) 218112000
- Percentage of total elements: 2.72%