84 KiB
84 KiB
Watt-Tool-8B-IQ4_NL.gguf - GGUF Internal File Dump
- Endian: LITTLE endian
Key Value Metadata Store
There are 43 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 | 40 |
| 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 | llama.vocab_size | 128256 |
| 28 | UINT32 | 1 | llama.rope.dimension_count | 128 |
| 29 | STRING | 1 | tokenizer.ggml.model | gpt2 |
| 30 | STRING | 1 | tokenizer.ggml.pre | llama-bpe |
| 31 | [STRING] | 128256 | tokenizer.ggml.tokens | [ !, ", #, $, %, ... ] |
| 32 | [INT32] | 128256 | tokenizer.ggml.token_type | [ 1, 1, 1, 1, 1, 1, 1, ... ] |
| 33 | [STRING] | 280147 | tokenizer.ggml.merges | [ Ġ Ġ, Ġ ĠĠĠ, ĠĠ ĠĠ, ĠĠĠ Ġ, i n, ... ] |
| 34 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 128000 |
| 35 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 128009 |
| 36 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 128009 |
| 37 | STRING | 1 | tokenizer.chat_template | `{{ '< |
| 38 | UINT32 | 1 | general.quantization_version | 2 |
| 39 | UINT32 | 1 | general.file_type | 25 |
| 40 | STRING | 1 | quantize.imatrix.file | ./imatrix/imatrix-Watt-Tool-8B-small.dat |
| 41 | STRING | 1 | quantize.imatrix.dataset | ../../datasets/imatrix/calibration_eur_small.txt |
| 42 | INT32 | 1 | quantize.imatrix.entries_count | 225 |
| 43 | INT32 | 1 | quantize.imatrix.chunks_count | 962 |
Tensors Overview ~8B Elements
Total number of elements in all tensors: 8030261312 Elements
- Watt-Tool-8B-IQ4_NL.gguf - GGUF Internal File Dump
- Key Value Metadata Store
- Tensors Overview ~8B Elements
- Tensor Data Offset
- Base Tensor Group : ~1B Elements
- Block 0 Tensor Group : ~218M Elements
- Block 1 Tensor Group : ~218M Elements
- Block 2 Tensor Group : ~218M Elements
- Block 3 Tensor Group : ~218M Elements
- Block 4 Tensor Group : ~218M Elements
- Block 5 Tensor Group : ~218M Elements
- Block 6 Tensor Group : ~218M Elements
- Block 7 Tensor Group : ~218M Elements
- Block 8 Tensor Group : ~218M Elements
- Block 9 Tensor Group : ~218M Elements
- Block 10 Tensor Group : ~218M Elements
- Block 11 Tensor Group : ~218M Elements
- Block 12 Tensor Group : ~218M Elements
- Block 13 Tensor Group : ~218M Elements
- Block 14 Tensor Group : ~218M Elements
- Block 15 Tensor Group : ~218M Elements
- Block 16 Tensor Group : ~218M Elements
- Block 17 Tensor Group : ~218M Elements
- Block 18 Tensor Group : ~218M Elements
- Block 19 Tensor Group : ~218M Elements
- Block 20 Tensor Group : ~218M Elements
- Block 21 Tensor Group : ~218M Elements
- Block 22 Tensor Group : ~218M Elements
- Block 23 Tensor Group : ~218M Elements
- Block 24 Tensor Group : ~218M Elements
- Block 25 Tensor Group : ~218M Elements
- Block 26 Tensor Group : ~218M Elements
- Block 27 Tensor Group : ~218M Elements
- Block 28 Tensor Group : ~218M Elements
- Block 29 Tensor Group : ~218M Elements
- Block 30 Tensor Group : ~218M Elements
- Block 31 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 | output.weight | 0x779620 | 0x119d0000 |
| 1 | output_norm.weight | 0x12149620 | 0x4000 |
| 2 | rope_freqs.weight | 0x1214d620 | 0x100 |
| 3 | token_embd.weight | 0x1214d720 | 0xd746000 |
| 4 | blk.0.attn_k.weight | 0x1f893720 | 0x1b8000 |
| 5 | blk.0.attn_norm.weight | 0x1fa4b720 | 0x4000 |
| 6 | blk.0.attn_output.weight | 0x1fa4f720 | 0x900000 |
| 7 | blk.0.attn_q.weight | 0x2034f720 | 0x6e0000 |
| 8 | blk.0.attn_v.weight | 0x20a2f720 | 0x220000 |
| 9 | blk.0.ffn_down.weight | 0x20c4f720 | 0x2680000 |
| 10 | blk.0.ffn_gate.weight | 0x232cf720 | 0x1810000 |
| 11 | blk.0.ffn_norm.weight | 0x24adf720 | 0x4000 |
| 12 | blk.0.ffn_up.weight | 0x24ae3720 | 0x1810000 |
| 13 | blk.1.attn_k.weight | 0x262f3720 | 0x1b8000 |
| 14 | blk.1.attn_norm.weight | 0x264ab720 | 0x4000 |
| 15 | blk.1.attn_output.weight | 0x264af720 | 0x900000 |
| 16 | blk.1.attn_q.weight | 0x26daf720 | 0x6e0000 |
| 17 | blk.1.attn_v.weight | 0x2748f720 | 0x220000 |
| 18 | blk.1.ffn_down.weight | 0x276af720 | 0x2680000 |
| 19 | blk.1.ffn_gate.weight | 0x29d2f720 | 0x1810000 |
| 20 | blk.1.ffn_norm.weight | 0x2b53f720 | 0x4000 |
| 21 | blk.1.ffn_up.weight | 0x2b543720 | 0x1810000 |
| 22 | blk.2.attn_k.weight | 0x2cd53720 | 0x1b8000 |
| 23 | blk.2.attn_norm.weight | 0x2cf0b720 | 0x4000 |
| 24 | blk.2.attn_output.weight | 0x2cf0f720 | 0x900000 |
| 25 | blk.2.attn_q.weight | 0x2d80f720 | 0x6e0000 |
| 26 | blk.2.attn_v.weight | 0x2deef720 | 0x220000 |
| 27 | blk.2.ffn_down.weight | 0x2e10f720 | 0x2680000 |
| 28 | blk.2.ffn_gate.weight | 0x3078f720 | 0x1810000 |
| 29 | blk.2.ffn_norm.weight | 0x31f9f720 | 0x4000 |
| 30 | blk.2.ffn_up.weight | 0x31fa3720 | 0x1810000 |
| 31 | blk.3.attn_k.weight | 0x337b3720 | 0x1b8000 |
| 32 | blk.3.attn_norm.weight | 0x3396b720 | 0x4000 |
| 33 | blk.3.attn_output.weight | 0x3396f720 | 0x900000 |
| 34 | blk.3.attn_q.weight | 0x3426f720 | 0x6e0000 |
| 35 | blk.3.attn_v.weight | 0x3494f720 | 0x220000 |
| 36 | blk.3.ffn_down.weight | 0x34b6f720 | 0x2680000 |
| 37 | blk.3.ffn_gate.weight | 0x371ef720 | 0x1810000 |
| 38 | blk.3.ffn_norm.weight | 0x389ff720 | 0x4000 |
| 39 | blk.3.ffn_up.weight | 0x38a03720 | 0x1810000 |
| 40 | blk.4.attn_k.weight | 0x3a213720 | 0x1b8000 |
| 41 | blk.4.attn_norm.weight | 0x3a3cb720 | 0x4000 |
| 42 | blk.4.attn_output.weight | 0x3a3cf720 | 0x900000 |
| 43 | blk.4.attn_q.weight | 0x3accf720 | 0x6e0000 |
| 44 | blk.4.attn_v.weight | 0x3b3af720 | 0x220000 |
| 45 | blk.4.ffn_down.weight | 0x3b5cf720 | 0x2680000 |
| 46 | blk.4.ffn_gate.weight | 0x3dc4f720 | 0x1810000 |
| 47 | blk.4.ffn_norm.weight | 0x3f45f720 | 0x4000 |
| 48 | blk.4.ffn_up.weight | 0x3f463720 | 0x1810000 |
| 49 | blk.5.attn_k.weight | 0x40c73720 | 0x1b8000 |
| 50 | blk.5.attn_norm.weight | 0x40e2b720 | 0x4000 |
| 51 | blk.5.attn_output.weight | 0x40e2f720 | 0x900000 |
| 52 | blk.5.attn_q.weight | 0x4172f720 | 0x6e0000 |
| 53 | blk.5.attn_v.weight | 0x41e0f720 | 0x220000 |
| 54 | blk.5.ffn_down.weight | 0x4202f720 | 0x2680000 |
| 55 | blk.5.ffn_gate.weight | 0x446af720 | 0x1810000 |
| 56 | blk.5.ffn_norm.weight | 0x45ebf720 | 0x4000 |
| 57 | blk.5.ffn_up.weight | 0x45ec3720 | 0x1810000 |
| 58 | blk.6.attn_k.weight | 0x476d3720 | 0x1b8000 |
| 59 | blk.6.attn_norm.weight | 0x4788b720 | 0x4000 |
| 60 | blk.6.attn_output.weight | 0x4788f720 | 0x900000 |
| 61 | blk.6.attn_q.weight | 0x4818f720 | 0x6e0000 |
| 62 | blk.6.attn_v.weight | 0x4886f720 | 0x220000 |
| 63 | blk.6.ffn_down.weight | 0x48a8f720 | 0x2680000 |
| 64 | blk.6.ffn_gate.weight | 0x4b10f720 | 0x1810000 |
| 65 | blk.6.ffn_norm.weight | 0x4c91f720 | 0x4000 |
| 66 | blk.6.ffn_up.weight | 0x4c923720 | 0x1810000 |
| 67 | blk.7.attn_k.weight | 0x4e133720 | 0x1b8000 |
| 68 | blk.7.attn_norm.weight | 0x4e2eb720 | 0x4000 |
| 69 | blk.7.attn_output.weight | 0x4e2ef720 | 0x900000 |
| 70 | blk.7.attn_q.weight | 0x4ebef720 | 0x6e0000 |
| 71 | blk.7.attn_v.weight | 0x4f2cf720 | 0x220000 |
| 72 | blk.7.ffn_down.weight | 0x4f4ef720 | 0x2680000 |
| 73 | blk.7.ffn_gate.weight | 0x51b6f720 | 0x1810000 |
| 74 | blk.7.ffn_norm.weight | 0x5337f720 | 0x4000 |
| 75 | blk.7.ffn_up.weight | 0x53383720 | 0x1810000 |
| 76 | blk.8.attn_k.weight | 0x54b93720 | 0x1b8000 |
| 77 | blk.8.attn_norm.weight | 0x54d4b720 | 0x4000 |
| 78 | blk.8.attn_output.weight | 0x54d4f720 | 0x900000 |
| 79 | blk.8.attn_q.weight | 0x5564f720 | 0x6e0000 |
| 80 | blk.8.attn_v.weight | 0x55d2f720 | 0x220000 |
| 81 | blk.8.ffn_down.weight | 0x55f4f720 | 0x2680000 |
| 82 | blk.8.ffn_gate.weight | 0x585cf720 | 0x1810000 |
| 83 | blk.8.ffn_norm.weight | 0x59ddf720 | 0x4000 |
| 84 | blk.8.ffn_up.weight | 0x59de3720 | 0x1810000 |
| 85 | blk.9.attn_k.weight | 0x5b5f3720 | 0x1b8000 |
| 86 | blk.9.attn_norm.weight | 0x5b7ab720 | 0x4000 |
| 87 | blk.9.attn_output.weight | 0x5b7af720 | 0x900000 |
| 88 | blk.9.attn_q.weight | 0x5c0af720 | 0x6e0000 |
| 89 | blk.9.attn_v.weight | 0x5c78f720 | 0x220000 |
| 90 | blk.9.ffn_down.weight | 0x5c9af720 | 0x2680000 |
| 91 | blk.9.ffn_gate.weight | 0x5f02f720 | 0x1810000 |
| 92 | blk.9.ffn_norm.weight | 0x6083f720 | 0x4000 |
| 93 | blk.9.ffn_up.weight | 0x60843720 | 0x1810000 |
| 94 | blk.10.attn_k.weight | 0x62053720 | 0x1b8000 |
| 95 | blk.10.attn_norm.weight | 0x6220b720 | 0x4000 |
| 96 | blk.10.attn_output.weight | 0x6220f720 | 0x900000 |
| 97 | blk.10.attn_q.weight | 0x62b0f720 | 0x6e0000 |
| 98 | blk.10.attn_v.weight | 0x631ef720 | 0x220000 |
| 99 | blk.10.ffn_down.weight | 0x6340f720 | 0x2680000 |
| 100 | blk.10.ffn_gate.weight | 0x65a8f720 | 0x1810000 |
| 101 | blk.10.ffn_norm.weight | 0x6729f720 | 0x4000 |
| 102 | blk.10.ffn_up.weight | 0x672a3720 | 0x1810000 |
| 103 | blk.11.attn_k.weight | 0x68ab3720 | 0x1b8000 |
| 104 | blk.11.attn_norm.weight | 0x68c6b720 | 0x4000 |
| 105 | blk.11.attn_output.weight | 0x68c6f720 | 0x900000 |
| 106 | blk.11.attn_q.weight | 0x6956f720 | 0x6e0000 |
| 107 | blk.11.attn_v.weight | 0x69c4f720 | 0x220000 |
| 108 | blk.11.ffn_down.weight | 0x69e6f720 | 0x2680000 |
| 109 | blk.11.ffn_gate.weight | 0x6c4ef720 | 0x1810000 |
| 110 | blk.11.ffn_norm.weight | 0x6dcff720 | 0x4000 |
| 111 | blk.11.ffn_up.weight | 0x6dd03720 | 0x1810000 |
| 112 | blk.12.attn_k.weight | 0x6f513720 | 0x1b8000 |
| 113 | blk.12.attn_norm.weight | 0x6f6cb720 | 0x4000 |
| 114 | blk.12.attn_output.weight | 0x6f6cf720 | 0x900000 |
| 115 | blk.12.attn_q.weight | 0x6ffcf720 | 0x6e0000 |
| 116 | blk.12.attn_v.weight | 0x706af720 | 0x220000 |
| 117 | blk.12.ffn_down.weight | 0x708cf720 | 0x2680000 |
| 118 | blk.12.ffn_gate.weight | 0x72f4f720 | 0x1810000 |
| 119 | blk.12.ffn_norm.weight | 0x7475f720 | 0x4000 |
| 120 | blk.12.ffn_up.weight | 0x74763720 | 0x1810000 |
| 121 | blk.13.attn_k.weight | 0x75f73720 | 0x240000 |
| 122 | blk.13.attn_norm.weight | 0x761b3720 | 0x4000 |
| 123 | blk.13.attn_output.weight | 0x761b7720 | 0x900000 |
| 124 | blk.13.attn_q.weight | 0x76ab7720 | 0x900000 |
| 125 | blk.13.attn_v.weight | 0x773b7720 | 0x240000 |
| 126 | blk.13.ffn_down.weight | 0x775f7720 | 0x2680000 |
| 127 | blk.13.ffn_gate.weight | 0x79c77720 | 0x1810000 |
| 128 | blk.13.ffn_norm.weight | 0x7b487720 | 0x4000 |
| 129 | blk.13.ffn_up.weight | 0x7b48b720 | 0x1810000 |
| 130 | blk.14.attn_k.weight | 0x7cc9b720 | 0x240000 |
| 131 | blk.14.attn_norm.weight | 0x7cedb720 | 0x4000 |
| 132 | blk.14.attn_output.weight | 0x7cedf720 | 0x900000 |
| 133 | blk.14.attn_q.weight | 0x7d7df720 | 0x900000 |
| 134 | blk.14.attn_v.weight | 0x7e0df720 | 0x240000 |
| 135 | blk.14.ffn_down.weight | 0x7e31f720 | 0x2680000 |
| 136 | blk.14.ffn_gate.weight | 0x8099f720 | 0x1810000 |
| 137 | blk.14.ffn_norm.weight | 0x821af720 | 0x4000 |
| 138 | blk.14.ffn_up.weight | 0x821b3720 | 0x1810000 |
| 139 | blk.15.attn_k.weight | 0x839c3720 | 0x1b8000 |
| 140 | blk.15.attn_norm.weight | 0x83b7b720 | 0x4000 |
| 141 | blk.15.attn_output.weight | 0x83b7f720 | 0x900000 |
| 142 | blk.15.attn_q.weight | 0x8447f720 | 0x6e0000 |
| 143 | blk.15.attn_v.weight | 0x84b5f720 | 0x220000 |
| 144 | blk.15.ffn_down.weight | 0x84d7f720 | 0x2680000 |
| 145 | blk.15.ffn_gate.weight | 0x873ff720 | 0x1810000 |
| 146 | blk.15.ffn_norm.weight | 0x88c0f720 | 0x4000 |
| 147 | blk.15.ffn_up.weight | 0x88c13720 | 0x1810000 |
| 148 | blk.16.attn_k.weight | 0x8a423720 | 0x240000 |
| 149 | blk.16.attn_norm.weight | 0x8a663720 | 0x4000 |
| 150 | blk.16.attn_output.weight | 0x8a667720 | 0x900000 |
| 151 | blk.16.attn_q.weight | 0x8af67720 | 0x900000 |
| 152 | blk.16.attn_v.weight | 0x8b867720 | 0x240000 |
| 153 | blk.16.ffn_down.weight | 0x8baa7720 | 0x2680000 |
| 154 | blk.16.ffn_gate.weight | 0x8e127720 | 0x1f80000 |
| 155 | blk.16.ffn_norm.weight | 0x900a7720 | 0x4000 |
| 156 | blk.16.ffn_up.weight | 0x900ab720 | 0x1f80000 |
| 157 | blk.17.attn_k.weight | 0x9202b720 | 0x1b8000 |
| 158 | blk.17.attn_norm.weight | 0x921e3720 | 0x4000 |
| 159 | blk.17.attn_output.weight | 0x921e7720 | 0x900000 |
| 160 | blk.17.attn_q.weight | 0x92ae7720 | 0x6e0000 |
| 161 | blk.17.attn_v.weight | 0x931c7720 | 0x220000 |
| 162 | blk.17.ffn_down.weight | 0x933e7720 | 0x2680000 |
| 163 | blk.17.ffn_gate.weight | 0x95a67720 | 0x1f80000 |
| 164 | blk.17.ffn_norm.weight | 0x979e7720 | 0x4000 |
| 165 | blk.17.ffn_up.weight | 0x979eb720 | 0x1f80000 |
| 166 | blk.18.attn_k.weight | 0x9996b720 | 0x240000 |
| 167 | blk.18.attn_norm.weight | 0x99bab720 | 0x4000 |
| 168 | blk.18.attn_output.weight | 0x99baf720 | 0x900000 |
| 169 | blk.18.attn_q.weight | 0x9a4af720 | 0x900000 |
| 170 | blk.18.attn_v.weight | 0x9adaf720 | 0x240000 |
| 171 | blk.18.ffn_down.weight | 0x9afef720 | 0x2680000 |
| 172 | blk.18.ffn_gate.weight | 0x9d66f720 | 0x1f80000 |
| 173 | blk.18.ffn_norm.weight | 0x9f5ef720 | 0x4000 |
| 174 | blk.18.ffn_up.weight | 0x9f5f3720 | 0x1f80000 |
| 175 | blk.19.attn_k.weight | 0xa1573720 | 0x240000 |
| 176 | blk.19.attn_norm.weight | 0xa17b3720 | 0x4000 |
| 177 | blk.19.attn_output.weight | 0xa17b7720 | 0x900000 |
| 178 | blk.19.attn_q.weight | 0xa20b7720 | 0x900000 |
| 179 | blk.19.attn_v.weight | 0xa29b7720 | 0x240000 |
| 180 | blk.19.ffn_down.weight | 0xa2bf7720 | 0x2680000 |
| 181 | blk.19.ffn_gate.weight | 0xa5277720 | 0x1f80000 |
| 182 | blk.19.ffn_norm.weight | 0xa71f7720 | 0x4000 |
| 183 | blk.19.ffn_up.weight | 0xa71fb720 | 0x1f80000 |
| 184 | blk.20.attn_k.weight | 0xa917b720 | 0x240000 |
| 185 | blk.20.attn_norm.weight | 0xa93bb720 | 0x4000 |
| 186 | blk.20.attn_output.weight | 0xa93bf720 | 0x900000 |
| 187 | blk.20.attn_q.weight | 0xa9cbf720 | 0x900000 |
| 188 | blk.20.attn_v.weight | 0xaa5bf720 | 0x240000 |
| 189 | blk.20.ffn_down.weight | 0xaa7ff720 | 0x2680000 |
| 190 | blk.20.ffn_gate.weight | 0xace7f720 | 0x1f80000 |
| 191 | blk.20.ffn_norm.weight | 0xaedff720 | 0x4000 |
| 192 | blk.20.ffn_up.weight | 0xaee03720 | 0x1f80000 |
| 193 | blk.21.attn_k.weight | 0xb0d83720 | 0x240000 |
| 194 | blk.21.attn_norm.weight | 0xb0fc3720 | 0x4000 |
| 195 | blk.21.attn_output.weight | 0xb0fc7720 | 0x900000 |
| 196 | blk.21.attn_q.weight | 0xb18c7720 | 0x900000 |
| 197 | blk.21.attn_v.weight | 0xb21c7720 | 0x240000 |
| 198 | blk.21.ffn_down.weight | 0xb2407720 | 0x2680000 |
| 199 | blk.21.ffn_gate.weight | 0xb4a87720 | 0x1f80000 |
| 200 | blk.21.ffn_norm.weight | 0xb6a07720 | 0x4000 |
| 201 | blk.21.ffn_up.weight | 0xb6a0b720 | 0x1f80000 |
| 202 | blk.22.attn_k.weight | 0xb898b720 | 0x240000 |
| 203 | blk.22.attn_norm.weight | 0xb8bcb720 | 0x4000 |
| 204 | blk.22.attn_output.weight | 0xb8bcf720 | 0x900000 |
| 205 | blk.22.attn_q.weight | 0xb94cf720 | 0x900000 |
| 206 | blk.22.attn_v.weight | 0xb9dcf720 | 0x240000 |
| 207 | blk.22.ffn_down.weight | 0xba00f720 | 0x2680000 |
| 208 | blk.22.ffn_gate.weight | 0xbc68f720 | 0x1f80000 |
| 209 | blk.22.ffn_norm.weight | 0xbe60f720 | 0x4000 |
| 210 | blk.22.ffn_up.weight | 0xbe613720 | 0x1f80000 |
| 211 | blk.23.attn_k.weight | 0xc0593720 | 0x240000 |
| 212 | blk.23.attn_norm.weight | 0xc07d3720 | 0x4000 |
| 213 | blk.23.attn_output.weight | 0xc07d7720 | 0x900000 |
| 214 | blk.23.attn_q.weight | 0xc10d7720 | 0x900000 |
| 215 | blk.23.attn_v.weight | 0xc19d7720 | 0x240000 |
| 216 | blk.23.ffn_down.weight | 0xc1c17720 | 0x2680000 |
| 217 | blk.23.ffn_gate.weight | 0xc4297720 | 0x1f80000 |
| 218 | blk.23.ffn_norm.weight | 0xc6217720 | 0x4000 |
| 219 | blk.23.ffn_up.weight | 0xc621b720 | 0x1f80000 |
| 220 | blk.24.attn_k.weight | 0xc819b720 | 0x240000 |
| 221 | blk.24.attn_norm.weight | 0xc83db720 | 0x4000 |
| 222 | blk.24.attn_output.weight | 0xc83df720 | 0x900000 |
| 223 | blk.24.attn_q.weight | 0xc8cdf720 | 0x900000 |
| 224 | blk.24.attn_v.weight | 0xc95df720 | 0x240000 |
| 225 | blk.24.ffn_down.weight | 0xc981f720 | 0x2680000 |
| 226 | blk.24.ffn_gate.weight | 0xcbe9f720 | 0x1f80000 |
| 227 | blk.24.ffn_norm.weight | 0xcde1f720 | 0x4000 |
| 228 | blk.24.ffn_up.weight | 0xcde23720 | 0x1f80000 |
| 229 | blk.25.attn_k.weight | 0xcfda3720 | 0x240000 |
| 230 | blk.25.attn_norm.weight | 0xcffe3720 | 0x4000 |
| 231 | blk.25.attn_output.weight | 0xcffe7720 | 0x900000 |
| 232 | blk.25.attn_q.weight | 0xd08e7720 | 0x900000 |
| 233 | blk.25.attn_v.weight | 0xd11e7720 | 0x240000 |
| 234 | blk.25.ffn_down.weight | 0xd1427720 | 0x2680000 |
| 235 | blk.25.ffn_gate.weight | 0xd3aa7720 | 0x1f80000 |
| 236 | blk.25.ffn_norm.weight | 0xd5a27720 | 0x4000 |
| 237 | blk.25.ffn_up.weight | 0xd5a2b720 | 0x1f80000 |
| 238 | blk.26.attn_k.weight | 0xd79ab720 | 0x240000 |
| 239 | blk.26.attn_norm.weight | 0xd7beb720 | 0x4000 |
| 240 | blk.26.attn_output.weight | 0xd7bef720 | 0x900000 |
| 241 | blk.26.attn_q.weight | 0xd84ef720 | 0x900000 |
| 242 | blk.26.attn_v.weight | 0xd8def720 | 0x240000 |
| 243 | blk.26.ffn_down.weight | 0xd902f720 | 0x2680000 |
| 244 | blk.26.ffn_gate.weight | 0xdb6af720 | 0x1f80000 |
| 245 | blk.26.ffn_norm.weight | 0xdd62f720 | 0x4000 |
| 246 | blk.26.ffn_up.weight | 0xdd633720 | 0x1f80000 |
| 247 | blk.27.attn_k.weight | 0xdf5b3720 | 0x240000 |
| 248 | blk.27.attn_norm.weight | 0xdf7f3720 | 0x4000 |
| 249 | blk.27.attn_output.weight | 0xdf7f7720 | 0x900000 |
| 250 | blk.27.attn_q.weight | 0xe00f7720 | 0x900000 |
| 251 | blk.27.attn_v.weight | 0xe09f7720 | 0x240000 |
| 252 | blk.27.ffn_down.weight | 0xe0c37720 | 0x2680000 |
| 253 | blk.27.ffn_gate.weight | 0xe32b7720 | 0x1f80000 |
| 254 | blk.27.ffn_norm.weight | 0xe5237720 | 0x4000 |
| 255 | blk.27.ffn_up.weight | 0xe523b720 | 0x1f80000 |
| 256 | blk.28.attn_k.weight | 0xe71bb720 | 0x240000 |
| 257 | blk.28.attn_norm.weight | 0xe73fb720 | 0x4000 |
| 258 | blk.28.attn_output.weight | 0xe73ff720 | 0x900000 |
| 259 | blk.28.attn_q.weight | 0xe7cff720 | 0x900000 |
| 260 | blk.28.attn_v.weight | 0xe85ff720 | 0x240000 |
| 261 | blk.28.ffn_down.weight | 0xe883f720 | 0x2680000 |
| 262 | blk.28.ffn_gate.weight | 0xeaebf720 | 0x1f80000 |
| 263 | blk.28.ffn_norm.weight | 0xece3f720 | 0x4000 |
| 264 | blk.28.ffn_up.weight | 0xece43720 | 0x1f80000 |
| 265 | blk.29.attn_k.weight | 0xeedc3720 | 0x240000 |
| 266 | blk.29.attn_norm.weight | 0xef003720 | 0x4000 |
| 267 | blk.29.attn_output.weight | 0xef007720 | 0x900000 |
| 268 | blk.29.attn_q.weight | 0xef907720 | 0x900000 |
| 269 | blk.29.attn_v.weight | 0xf0207720 | 0x240000 |
| 270 | blk.29.ffn_down.weight | 0xf0447720 | 0x2680000 |
| 271 | blk.29.ffn_gate.weight | 0xf2ac7720 | 0x1f80000 |
| 272 | blk.29.ffn_norm.weight | 0xf4a47720 | 0x4000 |
| 273 | blk.29.ffn_up.weight | 0xf4a4b720 | 0x1f80000 |
| 274 | blk.30.attn_k.weight | 0xf69cb720 | 0x240000 |
| 275 | blk.30.attn_norm.weight | 0xf6c0b720 | 0x4000 |
| 276 | blk.30.attn_output.weight | 0xf6c0f720 | 0x900000 |
| 277 | blk.30.attn_q.weight | 0xf750f720 | 0x900000 |
| 278 | blk.30.attn_v.weight | 0xf7e0f720 | 0x240000 |
| 279 | blk.30.ffn_down.weight | 0xf804f720 | 0x2680000 |
| 280 | blk.30.ffn_gate.weight | 0xfa6cf720 | 0x1f80000 |
| 281 | blk.30.ffn_norm.weight | 0xfc64f720 | 0x4000 |
| 282 | blk.30.ffn_up.weight | 0xfc653720 | 0x1f80000 |
| 283 | blk.31.attn_k.weight | 0xfe5d3720 | 0x1b8000 |
| 284 | blk.31.attn_norm.weight | 0xfe78b720 | 0x4000 |
| 285 | blk.31.attn_output.weight | 0xfe78f720 | 0x900000 |
| 286 | blk.31.attn_q.weight | 0xff08f720 | 0x6e0000 |
| 287 | blk.31.attn_v.weight | 0xff76f720 | 0x220000 |
| 288 | blk.31.ffn_down.weight | 0xff98f720 | 0x2680000 |
| 289 | blk.31.ffn_gate.weight | 0x10200f720 | 0x1f80000 |
| 290 | blk.31.ffn_norm.weight | 0x103f8f720 | 0x4000 |
| 291 | blk.31.ffn_up.weight | 0x103f93720 | 0x1f80000 |
Base Tensor Group : ~1B Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 0 | output.weight | Output (W) | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ4_NL |
| 1 | output_norm.weight | Output Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 2 | rope_freqs.weight | Rope_Freqs (W) | ( 64) 64 | 64 x 1 x 1 x 1 | F32 |
| 3 | token_embd.weight | Token Embedding (W) | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 4 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 5 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 6 | blk.0.attn_output.weight | Block 0 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 7 | blk.0.attn_q.weight | Block 0 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 8 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 9 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 10 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 11 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 12 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 13 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 14 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 15 | blk.1.attn_output.weight | Block 1 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 16 | blk.1.attn_q.weight | Block 1 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 17 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 18 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 19 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 20 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 21 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.1: (~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 |
|---|---|---|---|---|---|
| 22 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 23 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 24 | blk.2.attn_output.weight | Block 2 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 25 | blk.2.attn_q.weight | Block 2 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 26 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 27 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 28 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 29 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 30 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.2: (~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 |
|---|---|---|---|---|---|
| 31 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 32 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 33 | blk.3.attn_output.weight | Block 3 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 34 | blk.3.attn_q.weight | Block 3 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 35 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 36 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 37 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 38 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 39 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.3: (~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 |
|---|---|---|---|---|---|
| 40 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 41 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 42 | blk.4.attn_output.weight | Block 4 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 43 | blk.4.attn_q.weight | Block 4 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 44 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 45 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 46 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 47 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 48 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 49 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 50 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 51 | blk.5.attn_output.weight | Block 5 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 52 | blk.5.attn_q.weight | Block 5 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 53 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 54 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 55 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 56 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 57 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 58 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 59 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 60 | blk.6.attn_output.weight | Block 6 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 61 | blk.6.attn_q.weight | Block 6 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 62 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 63 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 64 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 65 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 66 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 67 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 68 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 69 | blk.7.attn_output.weight | Block 7 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 70 | blk.7.attn_q.weight | Block 7 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 71 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 72 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 73 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 74 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 75 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 76 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 77 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 78 | blk.8.attn_output.weight | Block 8 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 79 | blk.8.attn_q.weight | Block 8 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 80 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 81 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 82 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 83 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 84 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 85 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 86 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 87 | blk.9.attn_output.weight | Block 9 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 88 | blk.9.attn_q.weight | Block 9 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 89 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 90 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 91 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 92 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 93 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- Total elements in blk.9: (~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 |
|---|---|---|---|---|---|
| 94 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 95 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 96 | blk.10.attn_output.weight | Block 10 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 97 | blk.10.attn_q.weight | Block 10 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 98 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 99 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 100 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 101 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 102 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 103 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 104 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 105 | blk.11.attn_output.weight | Block 11 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 106 | blk.11.attn_q.weight | Block 11 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 107 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 108 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 109 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 110 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 111 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 112 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 113 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 114 | blk.12.attn_output.weight | Block 12 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 115 | blk.12.attn_q.weight | Block 12 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 116 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 117 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 118 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 119 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 120 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 121 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 122 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 123 | blk.13.attn_output.weight | Block 13 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 124 | blk.13.attn_q.weight | Block 13 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 125 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 126 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 127 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 128 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 129 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 130 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 131 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 132 | blk.14.attn_output.weight | Block 14 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 133 | blk.14.attn_q.weight | Block 14 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 134 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 135 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 136 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 137 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 138 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 139 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 140 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 141 | blk.15.attn_output.weight | Block 15 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 142 | blk.15.attn_q.weight | Block 15 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 143 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 144 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 145 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
| 146 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 147 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S |
- 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 |
|---|---|---|---|---|---|
| 148 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 149 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 150 | blk.16.attn_output.weight | Block 16 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 151 | blk.16.attn_q.weight | Block 16 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 152 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 153 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 154 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 155 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 156 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 157 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 158 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 159 | blk.17.attn_output.weight | Block 17 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 160 | blk.17.attn_q.weight | Block 17 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 161 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 162 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 163 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 164 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 165 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 166 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 167 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 168 | blk.18.attn_output.weight | Block 18 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 169 | blk.18.attn_q.weight | Block 18 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 170 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 171 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 172 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 173 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 174 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 175 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 176 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 177 | blk.19.attn_output.weight | Block 19 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 178 | blk.19.attn_q.weight | Block 19 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 179 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 180 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 181 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 182 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 183 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- Total elements in blk.19: (~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 |
|---|---|---|---|---|---|
| 184 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 185 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 186 | blk.20.attn_output.weight | Block 20 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 187 | blk.20.attn_q.weight | Block 20 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 188 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 189 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 190 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 191 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 192 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 193 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 194 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 195 | blk.21.attn_output.weight | Block 21 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 196 | blk.21.attn_q.weight | Block 21 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 197 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 198 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 199 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 200 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 201 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 202 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 203 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 204 | blk.22.attn_output.weight | Block 22 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 205 | blk.22.attn_q.weight | Block 22 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 206 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 207 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 208 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 209 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 210 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 211 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 212 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 213 | blk.23.attn_output.weight | Block 23 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 214 | blk.23.attn_q.weight | Block 23 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 215 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 216 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 217 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 218 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 219 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 220 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 221 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 222 | blk.24.attn_output.weight | Block 24 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 223 | blk.24.attn_q.weight | Block 24 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 224 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 225 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 226 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 227 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 228 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 229 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 230 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 231 | blk.25.attn_output.weight | Block 25 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 232 | blk.25.attn_q.weight | Block 25 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 233 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 234 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 235 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 236 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 237 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 238 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 239 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 240 | blk.26.attn_output.weight | Block 26 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 241 | blk.26.attn_q.weight | Block 26 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 242 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 243 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 244 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 245 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 246 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 247 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 248 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 249 | blk.27.attn_output.weight | Block 27 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 250 | blk.27.attn_q.weight | Block 27 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 251 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 252 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 253 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 254 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 255 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 256 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 257 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 258 | blk.28.attn_output.weight | Block 28 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 259 | blk.28.attn_q.weight | Block 28 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 260 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 261 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 262 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 263 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 264 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 265 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 266 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 267 | blk.29.attn_output.weight | Block 29 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 268 | blk.29.attn_q.weight | Block 29 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 269 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 270 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 271 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 272 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 273 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- Total elements in blk.29: (~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 |
|---|---|---|---|---|---|
| 274 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 275 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 276 | blk.30.attn_output.weight | Block 30 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 277 | blk.30.attn_q.weight | Block 30 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 278 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL |
| 279 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 280 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 281 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 282 | blk.30.ffn_up.weight | Block 30 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- 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 |
|---|---|---|---|---|---|
| 283 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S |
| 284 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 285 | blk.31.attn_output.weight | Block 31 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL |
| 286 | blk.31.attn_q.weight | Block 31 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S |
| 287 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS |
| 288 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K |
| 289 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
| 290 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 |
| 291 | blk.31.ffn_up.weight | Block 31 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL |
- Total elements in blk.31: (~218M) 218112000
- Percentage of total elements: 2.72%