Qwen3-30B-A3B-Q3_K_S.gguf - GGUF Internal File Dump
- Endian: LITTLE endian
Key Value Metadata Store
There are 45 key-value pairs in this file
| POS | TYPE | Count | Key | Value |
|---|---|---|---|---|
| 1 | UINT32 | 1 | GGUF.version | 3 |
| 2 | UINT64 | 1 | GGUF.tensor_count | 555 |
| 3 | UINT64 | 1 | GGUF.kv_count | 42 |
| 4 | STRING | 1 | general.architecture | qwen3moe |
| 5 | STRING | 1 | general.type | model |
| 6 | STRING | 1 | general.name | Qwen3 30B A3B |
| 7 | STRING | 1 | general.basename | Qwen3 |
| 8 | STRING | 1 | general.size_label | 30B-A3B |
| 9 | STRING | 1 | general.license | apache-2.0 |
| 10 | STRING | 1 | general.license.link | https://huggingface.co/Qwen/Qwen3-30B-A3B/blob/main/LICENSE |
| 11 | UINT32 | 1 | general.base_model.count | 1 |
| 12 | STRING | 1 | general.base_model.0.name | Qwen3 30B A3B Base |
| 13 | STRING | 1 | general.base_model.0.organization | Qwen |
| 14 | STRING | 1 | general.base_model.0.repo_url | https://huggingface.co/Qwen/Qwen3-30B-A3B-Base |
| 15 | [STRING] | 1 | general.tags | [ text-generation ] |
| 16 | UINT32 | 1 | qwen3moe.context_length | 40960 |
| 17 | UINT32 | 1 | qwen3moe.embedding_length | 2048 |
| 18 | UINT32 | 1 | qwen3moe.feed_forward_length | 6144 |
| 19 | UINT32 | 1 | qwen3moe.attention.head_count | 32 |
| 20 | UINT32 | 1 | qwen3moe.attention.head_count_kv | 4 |
| 21 | FLOAT32 | 1 | qwen3moe.rope.freq_base | 1000000.0 |
| 22 | FLOAT32 | 1 | qwen3moe.attention.layer_norm_rms_epsilon | 1e-06 |
| 23 | UINT32 | 1 | qwen3moe.expert_used_count | 8 |
| 24 | UINT32 | 1 | qwen3moe.attention.key_length | 128 |
| 25 | UINT32 | 1 | qwen3moe.attention.value_length | 128 |
| 26 | UINT32 | 1 | qwen3moe.expert_count | 128 |
| 27 | UINT32 | 1 | qwen3moe.expert_feed_forward_length | 768 |
| 28 | STRING | 1 | tokenizer.ggml.model | gpt2 |
| 29 | STRING | 1 | tokenizer.ggml.pre | qwen2 |
| 30 | [STRING] | 151936 | tokenizer.ggml.tokens | [ !, ", #, $, %, ... ] |
| 31 | [INT32] | 151936 | tokenizer.ggml.token_type | [ 1, 1, 1, 1, 1, 1, 1, ... ] |
| 32 | [STRING] | 151387 | tokenizer.ggml.merges | [ Ġ Ġ, ĠĠ ĠĠ, i n, Ġ t, ĠĠĠĠ ĠĠĠĠ, ... ] |
| 33 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 151645 |
| 34 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 151643 |
| 35 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 151643 |
| 36 | BOOL | 1 | tokenizer.ggml.add_bos_token | False |
| 37 | STRING | 1 | tokenizer.chat_template | `{%- if tools %}{{- '< |
| 38 | UINT32 | 1 | general.quantization_version | 2 |
| 39 | UINT32 | 1 | general.file_type | 11 |
| 40 | BOOL | 1 | general.pruned | True |
| 41 | UINT32 | 1 | qwen3moe.block_count | 46 |
| 42 | STRING | 1 | quantize.imatrix.file | ./imatrix/imatrix-Qwen3-30B-A3B-medium.dat |
| 43 | STRING | 1 | quantize.imatrix.dataset | ../../datasets/imatrix/combined_all_medium.txt |
| 44 | INT32 | 1 | quantize.imatrix.entries_count | 385 |
| 45 | INT32 | 1 | quantize.imatrix.chunks_count | 6946 |
Tensors Overview ~29B Elements
Total number of elements in all tensors: 29285881344 Elements
- Qwen3-30B-A3B-Q3_K_S.gguf - GGUF Internal File Dump
- Key Value Metadata Store
- Tensors Overview ~29B Elements
- Tensor Data Offset
- Base Tensor Group : ~622M Elements
- Block 0 Tensor Group : ~623M Elements
- Block 1 Tensor Group : ~623M Elements
- Block 2 Tensor Group : ~623M Elements
- Block 3 Tensor Group : ~623M Elements
- Block 4 Tensor Group : ~623M Elements
- Block 5 Tensor Group : ~623M Elements
- Block 6 Tensor Group : ~623M Elements
- Block 7 Tensor Group : ~623M Elements
- Block 8 Tensor Group : ~623M Elements
- Block 9 Tensor Group : ~623M Elements
- Block 10 Tensor Group : ~623M Elements
- Block 11 Tensor Group : ~623M Elements
- Block 12 Tensor Group : ~623M Elements
- Block 13 Tensor Group : ~623M Elements
- Block 14 Tensor Group : ~623M Elements
- Block 15 Tensor Group : ~623M Elements
- Block 16 Tensor Group : ~623M Elements
- Block 17 Tensor Group : ~623M Elements
- Block 18 Tensor Group : ~623M Elements
- Block 19 Tensor Group : ~623M Elements
- Block 20 Tensor Group : ~623M Elements
- Block 21 Tensor Group : ~623M Elements
- Block 22 Tensor Group : ~623M Elements
- Block 23 Tensor Group : ~623M Elements
- Block 24 Tensor Group : ~623M Elements
- Block 25 Tensor Group : ~623M Elements
- Block 26 Tensor Group : ~623M Elements
- Block 27 Tensor Group : ~623M Elements
- Block 28 Tensor Group : ~623M Elements
- Block 29 Tensor Group : ~623M Elements
- Block 30 Tensor Group : ~623M Elements
- Block 31 Tensor Group : ~623M Elements
- Block 32 Tensor Group : ~623M Elements
- Block 33 Tensor Group : ~623M Elements
- Block 34 Tensor Group : ~623M Elements
- Block 35 Tensor Group : ~623M Elements
- Block 36 Tensor Group : ~623M Elements
- Block 37 Tensor Group : ~623M Elements
- Block 38 Tensor Group : ~623M Elements
- Block 39 Tensor Group : ~623M Elements
- Block 40 Tensor Group : ~623M Elements
- Block 41 Tensor Group : ~623M Elements
- Block 42 Tensor Group : ~623M Elements
- Block 43 Tensor Group : ~623M Elements
- Block 44 Tensor Group : ~623M Elements
- Block 45 Tensor Group : ~623M 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 | 0x5b12e0 | 0x7f82800 |
| 1 | output_norm.weight | 0x8533ae0 | 0x2000 |
| 2 | token_embd.weight | 0x8535ae0 | 0x615f000 |
| 3 | blk.0.attn_k.weight | 0xe694ae0 | 0x54000 |
| 4 | blk.0.attn_k_norm.weight | 0xe6e8ae0 | 0x200 |
| 5 | blk.0.attn_norm.weight | 0xe6e8ce0 | 0x2000 |
| 6 | blk.0.attn_output.weight | 0xe6eace0 | 0x370000 |
| 7 | blk.0.attn_q.weight | 0xea5ace0 | 0x2a0000 |
| 8 | blk.0.attn_q_norm.weight | 0xecface0 | 0x200 |
| 9 | blk.0.attn_v.weight | 0xecfaee0 | 0x6e000 |
| 10 | blk.0.ffn_down_exps.weight | 0xed68ee0 | 0x6c00000 |
| 11 | blk.0.ffn_gate_exps.weight | 0x15968ee0 | 0x3f00000 |
| 12 | blk.0.ffn_gate_inp.weight | 0x19868ee0 | 0x100000 |
| 13 | blk.0.ffn_norm.weight | 0x19968ee0 | 0x2000 |
| 14 | blk.0.ffn_up_exps.weight | 0x1996aee0 | 0x3f00000 |
| 15 | blk.1.attn_k.weight | 0x1d86aee0 | 0x54000 |
| 16 | blk.1.attn_k_norm.weight | 0x1d8beee0 | 0x200 |
| 17 | blk.1.attn_norm.weight | 0x1d8bf0e0 | 0x2000 |
| 18 | blk.1.attn_output.weight | 0x1d8c10e0 | 0x370000 |
| 19 | blk.1.attn_q.weight | 0x1dc310e0 | 0x2a0000 |
| 20 | blk.1.attn_q_norm.weight | 0x1ded10e0 | 0x200 |
| 21 | blk.1.attn_v.weight | 0x1ded12e0 | 0x6e000 |
| 22 | blk.1.ffn_down_exps.weight | 0x1df3f2e0 | 0x6c00000 |
| 23 | blk.1.ffn_gate_exps.weight | 0x24b3f2e0 | 0x3f00000 |
| 24 | blk.1.ffn_gate_inp.weight | 0x28a3f2e0 | 0x100000 |
| 25 | blk.1.ffn_norm.weight | 0x28b3f2e0 | 0x2000 |
| 26 | blk.1.ffn_up_exps.weight | 0x28b412e0 | 0x3f00000 |
| 27 | blk.2.attn_k.weight | 0x2ca412e0 | 0x54000 |
| 28 | blk.2.attn_k_norm.weight | 0x2ca952e0 | 0x200 |
| 29 | blk.2.attn_norm.weight | 0x2ca954e0 | 0x2000 |
| 30 | blk.2.attn_output.weight | 0x2ca974e0 | 0x370000 |
| 31 | blk.2.attn_q.weight | 0x2ce074e0 | 0x2a0000 |
| 32 | blk.2.attn_q_norm.weight | 0x2d0a74e0 | 0x200 |
| 33 | blk.2.attn_v.weight | 0x2d0a76e0 | 0x6e000 |
| 34 | blk.2.ffn_down_exps.weight | 0x2d1156e0 | 0x6c00000 |
| 35 | blk.2.ffn_gate_exps.weight | 0x33d156e0 | 0x3f00000 |
| 36 | blk.2.ffn_gate_inp.weight | 0x37c156e0 | 0x100000 |
| 37 | blk.2.ffn_norm.weight | 0x37d156e0 | 0x2000 |
| 38 | blk.2.ffn_up_exps.weight | 0x37d176e0 | 0x3f00000 |
| 39 | blk.3.attn_k.weight | 0x3bc176e0 | 0x54000 |
| 40 | blk.3.attn_k_norm.weight | 0x3bc6b6e0 | 0x200 |
| 41 | blk.3.attn_norm.weight | 0x3bc6b8e0 | 0x2000 |
| 42 | blk.3.attn_output.weight | 0x3bc6d8e0 | 0x370000 |
| 43 | blk.3.attn_q.weight | 0x3bfdd8e0 | 0x2a0000 |
| 44 | blk.3.attn_q_norm.weight | 0x3c27d8e0 | 0x200 |
| 45 | blk.3.attn_v.weight | 0x3c27dae0 | 0x6e000 |
| 46 | blk.3.ffn_down_exps.weight | 0x3c2ebae0 | 0x6c00000 |
| 47 | blk.3.ffn_gate_exps.weight | 0x42eebae0 | 0x3f00000 |
| 48 | blk.3.ffn_gate_inp.weight | 0x46debae0 | 0x100000 |
| 49 | blk.3.ffn_norm.weight | 0x46eebae0 | 0x2000 |
| 50 | blk.3.ffn_up_exps.weight | 0x46eedae0 | 0x3f00000 |
| 51 | blk.4.attn_k.weight | 0x4adedae0 | 0x54000 |
| 52 | blk.4.attn_k_norm.weight | 0x4ae41ae0 | 0x200 |
| 53 | blk.4.attn_norm.weight | 0x4ae41ce0 | 0x2000 |
| 54 | blk.4.attn_output.weight | 0x4ae43ce0 | 0x370000 |
| 55 | blk.4.attn_q.weight | 0x4b1b3ce0 | 0x2a0000 |
| 56 | blk.4.attn_q_norm.weight | 0x4b453ce0 | 0x200 |
| 57 | blk.4.attn_v.weight | 0x4b453ee0 | 0x6e000 |
| 58 | blk.4.ffn_down_exps.weight | 0x4b4c1ee0 | 0x6c00000 |
| 59 | blk.4.ffn_gate_exps.weight | 0x520c1ee0 | 0x3f00000 |
| 60 | blk.4.ffn_gate_inp.weight | 0x55fc1ee0 | 0x100000 |
| 61 | blk.4.ffn_norm.weight | 0x560c1ee0 | 0x2000 |
| 62 | blk.4.ffn_up_exps.weight | 0x560c3ee0 | 0x3f00000 |
| 63 | blk.5.attn_k.weight | 0x59fc3ee0 | 0x54000 |
| 64 | blk.5.attn_k_norm.weight | 0x5a017ee0 | 0x200 |
| 65 | blk.5.attn_norm.weight | 0x5a0180e0 | 0x2000 |
| 66 | blk.5.attn_output.weight | 0x5a01a0e0 | 0x370000 |
| 67 | blk.5.attn_q.weight | 0x5a38a0e0 | 0x2a0000 |
| 68 | blk.5.attn_q_norm.weight | 0x5a62a0e0 | 0x200 |
| 69 | blk.5.attn_v.weight | 0x5a62a2e0 | 0x6e000 |
| 70 | blk.5.ffn_down_exps.weight | 0x5a6982e0 | 0x6c00000 |
| 71 | blk.5.ffn_gate_exps.weight | 0x612982e0 | 0x3f00000 |
| 72 | blk.5.ffn_gate_inp.weight | 0x651982e0 | 0x100000 |
| 73 | blk.5.ffn_norm.weight | 0x652982e0 | 0x2000 |
| 74 | blk.5.ffn_up_exps.weight | 0x6529a2e0 | 0x3f00000 |
| 75 | blk.6.attn_k.weight | 0x6919a2e0 | 0x54000 |
| 76 | blk.6.attn_k_norm.weight | 0x691ee2e0 | 0x200 |
| 77 | blk.6.attn_norm.weight | 0x691ee4e0 | 0x2000 |
| 78 | blk.6.attn_output.weight | 0x691f04e0 | 0x370000 |
| 79 | blk.6.attn_q.weight | 0x695604e0 | 0x2a0000 |
| 80 | blk.6.attn_q_norm.weight | 0x698004e0 | 0x200 |
| 81 | blk.6.attn_v.weight | 0x698006e0 | 0x6e000 |
| 82 | blk.6.ffn_down_exps.weight | 0x6986e6e0 | 0x6c00000 |
| 83 | blk.6.ffn_gate_exps.weight | 0x7046e6e0 | 0x3f00000 |
| 84 | blk.6.ffn_gate_inp.weight | 0x7436e6e0 | 0x100000 |
| 85 | blk.6.ffn_norm.weight | 0x7446e6e0 | 0x2000 |
| 86 | blk.6.ffn_up_exps.weight | 0x744706e0 | 0x3f00000 |
| 87 | blk.7.attn_k.weight | 0x783706e0 | 0x54000 |
| 88 | blk.7.attn_k_norm.weight | 0x783c46e0 | 0x200 |
| 89 | blk.7.attn_norm.weight | 0x783c48e0 | 0x2000 |
| 90 | blk.7.attn_output.weight | 0x783c68e0 | 0x370000 |
| 91 | blk.7.attn_q.weight | 0x787368e0 | 0x2a0000 |
| 92 | blk.7.attn_q_norm.weight | 0x789d68e0 | 0x200 |
| 93 | blk.7.attn_v.weight | 0x789d6ae0 | 0x6e000 |
| 94 | blk.7.ffn_down_exps.weight | 0x78a44ae0 | 0x6c00000 |
| 95 | blk.7.ffn_gate_exps.weight | 0x7f644ae0 | 0x3f00000 |
| 96 | blk.7.ffn_gate_inp.weight | 0x83544ae0 | 0x100000 |
| 97 | blk.7.ffn_norm.weight | 0x83644ae0 | 0x2000 |
| 98 | blk.7.ffn_up_exps.weight | 0x83646ae0 | 0x3f00000 |
| 99 | blk.8.attn_k.weight | 0x87546ae0 | 0x54000 |
| 100 | blk.8.attn_k_norm.weight | 0x8759aae0 | 0x200 |
| 101 | blk.8.attn_norm.weight | 0x8759ace0 | 0x2000 |
| 102 | blk.8.attn_output.weight | 0x8759cce0 | 0x370000 |
| 103 | blk.8.attn_q.weight | 0x8790cce0 | 0x2a0000 |
| 104 | blk.8.attn_q_norm.weight | 0x87bacce0 | 0x200 |
| 105 | blk.8.attn_v.weight | 0x87bacee0 | 0x6e000 |
| 106 | blk.8.ffn_down_exps.weight | 0x87c1aee0 | 0x6c00000 |
| 107 | blk.8.ffn_gate_exps.weight | 0x8e81aee0 | 0x3f00000 |
| 108 | blk.8.ffn_gate_inp.weight | 0x9271aee0 | 0x100000 |
| 109 | blk.8.ffn_norm.weight | 0x9281aee0 | 0x2000 |
| 110 | blk.8.ffn_up_exps.weight | 0x9281cee0 | 0x3f00000 |
| 111 | blk.9.attn_k.weight | 0x9671cee0 | 0x54000 |
| 112 | blk.9.attn_k_norm.weight | 0x96770ee0 | 0x200 |
| 113 | blk.9.attn_norm.weight | 0x967710e0 | 0x2000 |
| 114 | blk.9.attn_output.weight | 0x967730e0 | 0x370000 |
| 115 | blk.9.attn_q.weight | 0x96ae30e0 | 0x2a0000 |
| 116 | blk.9.attn_q_norm.weight | 0x96d830e0 | 0x200 |
| 117 | blk.9.attn_v.weight | 0x96d832e0 | 0x6e000 |
| 118 | blk.9.ffn_down_exps.weight | 0x96df12e0 | 0x6c00000 |
| 119 | blk.9.ffn_gate_exps.weight | 0x9d9f12e0 | 0x3f00000 |
| 120 | blk.9.ffn_gate_inp.weight | 0xa18f12e0 | 0x100000 |
| 121 | blk.9.ffn_norm.weight | 0xa19f12e0 | 0x2000 |
| 122 | blk.9.ffn_up_exps.weight | 0xa19f32e0 | 0x3f00000 |
| 123 | blk.10.attn_k.weight | 0xa58f32e0 | 0x54000 |
| 124 | blk.10.attn_k_norm.weight | 0xa59472e0 | 0x200 |
| 125 | blk.10.attn_norm.weight | 0xa59474e0 | 0x2000 |
| 126 | blk.10.attn_output.weight | 0xa59494e0 | 0x370000 |
| 127 | blk.10.attn_q.weight | 0xa5cb94e0 | 0x2a0000 |
| 128 | blk.10.attn_q_norm.weight | 0xa5f594e0 | 0x200 |
| 129 | blk.10.attn_v.weight | 0xa5f596e0 | 0x6e000 |
| 130 | blk.10.ffn_down_exps.weight | 0xa5fc76e0 | 0x6c00000 |
| 131 | blk.10.ffn_gate_exps.weight | 0xacbc76e0 | 0x3f00000 |
| 132 | blk.10.ffn_gate_inp.weight | 0xb0ac76e0 | 0x100000 |
| 133 | blk.10.ffn_norm.weight | 0xb0bc76e0 | 0x2000 |
| 134 | blk.10.ffn_up_exps.weight | 0xb0bc96e0 | 0x3f00000 |
| 135 | blk.11.attn_k.weight | 0xb4ac96e0 | 0x54000 |
| 136 | blk.11.attn_k_norm.weight | 0xb4b1d6e0 | 0x200 |
| 137 | blk.11.attn_norm.weight | 0xb4b1d8e0 | 0x2000 |
| 138 | blk.11.attn_output.weight | 0xb4b1f8e0 | 0x370000 |
| 139 | blk.11.attn_q.weight | 0xb4e8f8e0 | 0x2a0000 |
| 140 | blk.11.attn_q_norm.weight | 0xb512f8e0 | 0x200 |
| 141 | blk.11.attn_v.weight | 0xb512fae0 | 0x6e000 |
| 142 | blk.11.ffn_down_exps.weight | 0xb519dae0 | 0x6c00000 |
| 143 | blk.11.ffn_gate_exps.weight | 0xbbd9dae0 | 0x3f00000 |
| 144 | blk.11.ffn_gate_inp.weight | 0xbfc9dae0 | 0x100000 |
| 145 | blk.11.ffn_norm.weight | 0xbfd9dae0 | 0x2000 |
| 146 | blk.11.ffn_up_exps.weight | 0xbfd9fae0 | 0x3f00000 |
| 147 | blk.12.attn_k.weight | 0xc3c9fae0 | 0x54000 |
| 148 | blk.12.attn_k_norm.weight | 0xc3cf3ae0 | 0x200 |
| 149 | blk.12.attn_norm.weight | 0xc3cf3ce0 | 0x2000 |
| 150 | blk.12.attn_output.weight | 0xc3cf5ce0 | 0x370000 |
| 151 | blk.12.attn_q.weight | 0xc4065ce0 | 0x2a0000 |
| 152 | blk.12.attn_q_norm.weight | 0xc4305ce0 | 0x200 |
| 153 | blk.12.attn_v.weight | 0xc4305ee0 | 0x6e000 |
| 154 | blk.12.ffn_down_exps.weight | 0xc4373ee0 | 0x6c00000 |
| 155 | blk.12.ffn_gate_exps.weight | 0xcaf73ee0 | 0x3f00000 |
| 156 | blk.12.ffn_gate_inp.weight | 0xcee73ee0 | 0x100000 |
| 157 | blk.12.ffn_norm.weight | 0xcef73ee0 | 0x2000 |
| 158 | blk.12.ffn_up_exps.weight | 0xcef75ee0 | 0x3f00000 |
| 159 | blk.13.attn_k.weight | 0xd2e75ee0 | 0x54000 |
| 160 | blk.13.attn_k_norm.weight | 0xd2ec9ee0 | 0x200 |
| 161 | blk.13.attn_norm.weight | 0xd2eca0e0 | 0x2000 |
| 162 | blk.13.attn_output.weight | 0xd2ecc0e0 | 0x370000 |
| 163 | blk.13.attn_q.weight | 0xd323c0e0 | 0x2a0000 |
| 164 | blk.13.attn_q_norm.weight | 0xd34dc0e0 | 0x200 |
| 165 | blk.13.attn_v.weight | 0xd34dc2e0 | 0x6e000 |
| 166 | blk.13.ffn_down_exps.weight | 0xd354a2e0 | 0x6c00000 |
| 167 | blk.13.ffn_gate_exps.weight | 0xda14a2e0 | 0x3f00000 |
| 168 | blk.13.ffn_gate_inp.weight | 0xde04a2e0 | 0x100000 |
| 169 | blk.13.ffn_norm.weight | 0xde14a2e0 | 0x2000 |
| 170 | blk.13.ffn_up_exps.weight | 0xde14c2e0 | 0x3f00000 |
| 171 | blk.14.attn_k.weight | 0xe204c2e0 | 0x54000 |
| 172 | blk.14.attn_k_norm.weight | 0xe20a02e0 | 0x200 |
| 173 | blk.14.attn_norm.weight | 0xe20a04e0 | 0x2000 |
| 174 | blk.14.attn_output.weight | 0xe20a24e0 | 0x370000 |
| 175 | blk.14.attn_q.weight | 0xe24124e0 | 0x2a0000 |
| 176 | blk.14.attn_q_norm.weight | 0xe26b24e0 | 0x200 |
| 177 | blk.14.attn_v.weight | 0xe26b26e0 | 0x6e000 |
| 178 | blk.14.ffn_down_exps.weight | 0xe27206e0 | 0x6c00000 |
| 179 | blk.14.ffn_gate_exps.weight | 0xe93206e0 | 0x3f00000 |
| 180 | blk.14.ffn_gate_inp.weight | 0xed2206e0 | 0x100000 |
| 181 | blk.14.ffn_norm.weight | 0xed3206e0 | 0x2000 |
| 182 | blk.14.ffn_up_exps.weight | 0xed3226e0 | 0x3f00000 |
| 183 | blk.15.attn_k.weight | 0xf12226e0 | 0x54000 |
| 184 | blk.15.attn_k_norm.weight | 0xf12766e0 | 0x200 |
| 185 | blk.15.attn_norm.weight | 0xf12768e0 | 0x2000 |
| 186 | blk.15.attn_output.weight | 0xf12788e0 | 0x370000 |
| 187 | blk.15.attn_q.weight | 0xf15e88e0 | 0x2a0000 |
| 188 | blk.15.attn_q_norm.weight | 0xf18888e0 | 0x200 |
| 189 | blk.15.attn_v.weight | 0xf1888ae0 | 0x6e000 |
| 190 | blk.15.ffn_down_exps.weight | 0xf18f6ae0 | 0x6c00000 |
| 191 | blk.15.ffn_gate_exps.weight | 0xf84f6ae0 | 0x3f00000 |
| 192 | blk.15.ffn_gate_inp.weight | 0xfc3f6ae0 | 0x100000 |
| 193 | blk.15.ffn_norm.weight | 0xfc4f6ae0 | 0x2000 |
| 194 | blk.15.ffn_up_exps.weight | 0xfc4f8ae0 | 0x3f00000 |
| 195 | blk.16.attn_k.weight | 0x1003f8ae0 | 0x54000 |
| 196 | blk.16.attn_k_norm.weight | 0x10044cae0 | 0x200 |
| 197 | blk.16.attn_norm.weight | 0x10044cce0 | 0x2000 |
| 198 | blk.16.attn_output.weight | 0x10044ece0 | 0x370000 |
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| 200 | blk.16.attn_q_norm.weight | 0x100a5ece0 | 0x200 |
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| 204 | blk.16.ffn_gate_inp.weight | 0x10b5ccee0 | 0x100000 |
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| 206 | blk.16.ffn_up_exps.weight | 0x10b6ceee0 | 0x3f00000 |
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| 209 | blk.17.attn_norm.weight | 0x10f6230e0 | 0x2000 |
| 210 | blk.17.attn_output.weight | 0x10f6250e0 | 0x370000 |
| 211 | blk.17.attn_q.weight | 0x10f9950e0 | 0x2a0000 |
| 212 | blk.17.attn_q_norm.weight | 0x10fc350e0 | 0x200 |
| 213 | blk.17.attn_v.weight | 0x10fc352e0 | 0x6e000 |
| 214 | blk.17.ffn_down_exps.weight | 0x10fca32e0 | 0x6c00000 |
| 215 | blk.17.ffn_gate_exps.weight | 0x1168a32e0 | 0x3f00000 |
| 216 | blk.17.ffn_gate_inp.weight | 0x11a7a32e0 | 0x100000 |
| 217 | blk.17.ffn_norm.weight | 0x11a8a32e0 | 0x2000 |
| 218 | blk.17.ffn_up_exps.weight | 0x11a8a52e0 | 0x3f00000 |
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| 221 | blk.18.attn_norm.weight | 0x11e7f94e0 | 0x2000 |
| 222 | blk.18.attn_output.weight | 0x11e7fb4e0 | 0x370000 |
| 223 | blk.18.attn_q.weight | 0x11eb6b4e0 | 0x2a0000 |
| 224 | blk.18.attn_q_norm.weight | 0x11ee0b4e0 | 0x200 |
| 225 | blk.18.attn_v.weight | 0x11ee0b6e0 | 0x6e000 |
| 226 | blk.18.ffn_down_exps.weight | 0x11ee796e0 | 0x6c00000 |
| 227 | blk.18.ffn_gate_exps.weight | 0x125a796e0 | 0x5280000 |
| 228 | blk.18.ffn_gate_inp.weight | 0x12acf96e0 | 0x100000 |
| 229 | blk.18.ffn_norm.weight | 0x12adf96e0 | 0x2000 |
| 230 | blk.18.ffn_up_exps.weight | 0x12adfb6e0 | 0x5280000 |
| 231 | blk.19.attn_k.weight | 0x13007b6e0 | 0x54000 |
| 232 | blk.19.attn_k_norm.weight | 0x1300cf6e0 | 0x200 |
| 233 | blk.19.attn_norm.weight | 0x1300cf8e0 | 0x2000 |
| 234 | blk.19.attn_output.weight | 0x1300d18e0 | 0x370000 |
| 235 | blk.19.attn_q.weight | 0x1304418e0 | 0x2a0000 |
| 236 | blk.19.attn_q_norm.weight | 0x1306e18e0 | 0x200 |
| 237 | blk.19.attn_v.weight | 0x1306e1ae0 | 0x6e000 |
| 238 | blk.19.ffn_down_exps.weight | 0x13074fae0 | 0x6c00000 |
| 239 | blk.19.ffn_gate_exps.weight | 0x13734fae0 | 0x3f00000 |
| 240 | blk.19.ffn_gate_inp.weight | 0x13b24fae0 | 0x100000 |
| 241 | blk.19.ffn_norm.weight | 0x13b34fae0 | 0x2000 |
| 242 | blk.19.ffn_up_exps.weight | 0x13b351ae0 | 0x3f00000 |
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| 244 | blk.20.attn_k_norm.weight | 0x13f2a5ae0 | 0x200 |
| 245 | blk.20.attn_norm.weight | 0x13f2a5ce0 | 0x2000 |
| 246 | blk.20.attn_output.weight | 0x13f2a7ce0 | 0x370000 |
| 247 | blk.20.attn_q.weight | 0x13f617ce0 | 0x2a0000 |
| 248 | blk.20.attn_q_norm.weight | 0x13f8b7ce0 | 0x200 |
| 249 | blk.20.attn_v.weight | 0x13f8b7ee0 | 0x6e000 |
| 250 | blk.20.ffn_down_exps.weight | 0x13f925ee0 | 0x6c00000 |
| 251 | blk.20.ffn_gate_exps.weight | 0x146525ee0 | 0x3f00000 |
| 252 | blk.20.ffn_gate_inp.weight | 0x14a425ee0 | 0x100000 |
| 253 | blk.20.ffn_norm.weight | 0x14a525ee0 | 0x2000 |
| 254 | blk.20.ffn_up_exps.weight | 0x14a527ee0 | 0x3f00000 |
| 255 | blk.21.attn_k.weight | 0x14e427ee0 | 0x54000 |
| 256 | blk.21.attn_k_norm.weight | 0x14e47bee0 | 0x200 |
| 257 | blk.21.attn_norm.weight | 0x14e47c0e0 | 0x2000 |
| 258 | blk.21.attn_output.weight | 0x14e47e0e0 | 0x370000 |
| 259 | blk.21.attn_q.weight | 0x14e7ee0e0 | 0x2a0000 |
| 260 | blk.21.attn_q_norm.weight | 0x14ea8e0e0 | 0x200 |
| 261 | blk.21.attn_v.weight | 0x14ea8e2e0 | 0x6e000 |
| 262 | blk.21.ffn_down_exps.weight | 0x14eafc2e0 | 0x6c00000 |
| 263 | blk.21.ffn_gate_exps.weight | 0x1556fc2e0 | 0x3f00000 |
| 264 | blk.21.ffn_gate_inp.weight | 0x1595fc2e0 | 0x100000 |
| 265 | blk.21.ffn_norm.weight | 0x1596fc2e0 | 0x2000 |
| 266 | blk.21.ffn_up_exps.weight | 0x1596fe2e0 | 0x3f00000 |
| 267 | blk.22.attn_k.weight | 0x15d5fe2e0 | 0x54000 |
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| 269 | blk.22.attn_norm.weight | 0x15d6524e0 | 0x2000 |
| 270 | blk.22.attn_output.weight | 0x15d6544e0 | 0x370000 |
| 271 | blk.22.attn_q.weight | 0x15d9c44e0 | 0x2a0000 |
| 272 | blk.22.attn_q_norm.weight | 0x15dc644e0 | 0x200 |
| 273 | blk.22.attn_v.weight | 0x15dc646e0 | 0x6e000 |
| 274 | blk.22.ffn_down_exps.weight | 0x15dcd26e0 | 0x6c00000 |
| 275 | blk.22.ffn_gate_exps.weight | 0x1648d26e0 | 0x3f00000 |
| 276 | blk.22.ffn_gate_inp.weight | 0x1687d26e0 | 0x100000 |
| 277 | blk.22.ffn_norm.weight | 0x1688d26e0 | 0x2000 |
| 278 | blk.22.ffn_up_exps.weight | 0x1688d46e0 | 0x3f00000 |
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| 280 | blk.23.attn_k_norm.weight | 0x16c8286e0 | 0x200 |
| 281 | blk.23.attn_norm.weight | 0x16c8288e0 | 0x2000 |
| 282 | blk.23.attn_output.weight | 0x16c82a8e0 | 0x370000 |
| 283 | blk.23.attn_q.weight | 0x16cb9a8e0 | 0x2a0000 |
| 284 | blk.23.attn_q_norm.weight | 0x16ce3a8e0 | 0x200 |
| 285 | blk.23.attn_v.weight | 0x16ce3aae0 | 0x6e000 |
| 286 | blk.23.ffn_down_exps.weight | 0x16cea8ae0 | 0x6c00000 |
| 287 | blk.23.ffn_gate_exps.weight | 0x173aa8ae0 | 0x3f00000 |
| 288 | blk.23.ffn_gate_inp.weight | 0x1779a8ae0 | 0x100000 |
| 289 | blk.23.ffn_norm.weight | 0x177aa8ae0 | 0x2000 |
| 290 | blk.23.ffn_up_exps.weight | 0x177aaaae0 | 0x3f00000 |
| 291 | blk.24.attn_k.weight | 0x17b9aaae0 | 0x6e000 |
| 292 | blk.24.attn_k_norm.weight | 0x17ba18ae0 | 0x200 |
| 293 | blk.24.attn_norm.weight | 0x17ba18ce0 | 0x2000 |
| 294 | blk.24.attn_output.weight | 0x17ba1ace0 | 0x370000 |
| 295 | blk.24.attn_q.weight | 0x17bd8ace0 | 0x370000 |
| 296 | blk.24.attn_q_norm.weight | 0x17c0face0 | 0x200 |
| 297 | blk.24.attn_v.weight | 0x17c0faee0 | 0x6e000 |
| 298 | blk.24.ffn_down_exps.weight | 0x17c168ee0 | 0x6c00000 |
| 299 | blk.24.ffn_gate_exps.weight | 0x182d68ee0 | 0x3f00000 |
| 300 | blk.24.ffn_gate_inp.weight | 0x186c68ee0 | 0x100000 |
| 301 | blk.24.ffn_norm.weight | 0x186d68ee0 | 0x2000 |
| 302 | blk.24.ffn_up_exps.weight | 0x186d6aee0 | 0x3f00000 |
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| 305 | blk.25.attn_norm.weight | 0x18acd90e0 | 0x2000 |
| 306 | blk.25.attn_output.weight | 0x18acdb0e0 | 0x370000 |
| 307 | blk.25.attn_q.weight | 0x18b04b0e0 | 0x370000 |
| 308 | blk.25.attn_q_norm.weight | 0x18b3bb0e0 | 0x200 |
| 309 | blk.25.attn_v.weight | 0x18b3bb2e0 | 0x6e000 |
| 310 | blk.25.ffn_down_exps.weight | 0x18b4292e0 | 0x6c00000 |
| 311 | blk.25.ffn_gate_exps.weight | 0x1920292e0 | 0x5280000 |
| 312 | blk.25.ffn_gate_inp.weight | 0x1972a92e0 | 0x100000 |
| 313 | blk.25.ffn_norm.weight | 0x1973a92e0 | 0x2000 |
| 314 | blk.25.ffn_up_exps.weight | 0x1973ab2e0 | 0x5280000 |
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| 317 | blk.26.attn_norm.weight | 0x19c6994e0 | 0x2000 |
| 318 | blk.26.attn_output.weight | 0x19c69b4e0 | 0x370000 |
| 319 | blk.26.attn_q.weight | 0x19ca0b4e0 | 0x370000 |
| 320 | blk.26.attn_q_norm.weight | 0x19cd7b4e0 | 0x200 |
| 321 | blk.26.attn_v.weight | 0x19cd7b6e0 | 0x6e000 |
| 322 | blk.26.ffn_down_exps.weight | 0x19cde96e0 | 0x6c00000 |
| 323 | blk.26.ffn_gate_exps.weight | 0x1a39e96e0 | 0x5280000 |
| 324 | blk.26.ffn_gate_inp.weight | 0x1a8c696e0 | 0x100000 |
| 325 | blk.26.ffn_norm.weight | 0x1a8d696e0 | 0x2000 |
| 326 | blk.26.ffn_up_exps.weight | 0x1a8d6b6e0 | 0x5280000 |
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| 328 | blk.27.attn_k_norm.weight | 0x1ae0596e0 | 0x200 |
| 329 | blk.27.attn_norm.weight | 0x1ae0598e0 | 0x2000 |
| 330 | blk.27.attn_output.weight | 0x1ae05b8e0 | 0x370000 |
| 331 | blk.27.attn_q.weight | 0x1ae3cb8e0 | 0x370000 |
| 332 | blk.27.attn_q_norm.weight | 0x1ae73b8e0 | 0x200 |
| 333 | blk.27.attn_v.weight | 0x1ae73bae0 | 0x6e000 |
| 334 | blk.27.ffn_down_exps.weight | 0x1ae7a9ae0 | 0x6c00000 |
| 335 | blk.27.ffn_gate_exps.weight | 0x1b53a9ae0 | 0x5280000 |
| 336 | blk.27.ffn_gate_inp.weight | 0x1ba629ae0 | 0x100000 |
| 337 | blk.27.ffn_norm.weight | 0x1ba729ae0 | 0x2000 |
| 338 | blk.27.ffn_up_exps.weight | 0x1ba72bae0 | 0x5280000 |
| 339 | blk.28.attn_k.weight | 0x1bf9abae0 | 0x6e000 |
| 340 | blk.28.attn_k_norm.weight | 0x1bfa19ae0 | 0x200 |
| 341 | blk.28.attn_norm.weight | 0x1bfa19ce0 | 0x2000 |
| 342 | blk.28.attn_output.weight | 0x1bfa1bce0 | 0x370000 |
| 343 | blk.28.attn_q.weight | 0x1bfd8bce0 | 0x370000 |
| 344 | blk.28.attn_q_norm.weight | 0x1c00fbce0 | 0x200 |
| 345 | blk.28.attn_v.weight | 0x1c00fbee0 | 0x6e000 |
| 346 | blk.28.ffn_down_exps.weight | 0x1c0169ee0 | 0x6c00000 |
| 347 | blk.28.ffn_gate_exps.weight | 0x1c6d69ee0 | 0x5280000 |
| 348 | blk.28.ffn_gate_inp.weight | 0x1cbfe9ee0 | 0x100000 |
| 349 | blk.28.ffn_norm.weight | 0x1cc0e9ee0 | 0x2000 |
| 350 | blk.28.ffn_up_exps.weight | 0x1cc0ebee0 | 0x5280000 |
| 351 | blk.29.attn_k.weight | 0x1d136bee0 | 0x6e000 |
| 352 | blk.29.attn_k_norm.weight | 0x1d13d9ee0 | 0x200 |
| 353 | blk.29.attn_norm.weight | 0x1d13da0e0 | 0x2000 |
| 354 | blk.29.attn_output.weight | 0x1d13dc0e0 | 0x370000 |
| 355 | blk.29.attn_q.weight | 0x1d174c0e0 | 0x370000 |
| 356 | blk.29.attn_q_norm.weight | 0x1d1abc0e0 | 0x200 |
| 357 | blk.29.attn_v.weight | 0x1d1abc2e0 | 0x6e000 |
| 358 | blk.29.ffn_down_exps.weight | 0x1d1b2a2e0 | 0x6c00000 |
| 359 | blk.29.ffn_gate_exps.weight | 0x1d872a2e0 | 0x5280000 |
| 360 | blk.29.ffn_gate_inp.weight | 0x1dd9aa2e0 | 0x100000 |
| 361 | blk.29.ffn_norm.weight | 0x1ddaaa2e0 | 0x2000 |
| 362 | blk.29.ffn_up_exps.weight | 0x1ddaac2e0 | 0x5280000 |
| 363 | blk.30.attn_k.weight | 0x1e2d2c2e0 | 0x6e000 |
| 364 | blk.30.attn_k_norm.weight | 0x1e2d9a2e0 | 0x200 |
| 365 | blk.30.attn_norm.weight | 0x1e2d9a4e0 | 0x2000 |
| 366 | blk.30.attn_output.weight | 0x1e2d9c4e0 | 0x370000 |
| 367 | blk.30.attn_q.weight | 0x1e310c4e0 | 0x370000 |
| 368 | blk.30.attn_q_norm.weight | 0x1e347c4e0 | 0x200 |
| 369 | blk.30.attn_v.weight | 0x1e347c6e0 | 0x6e000 |
| 370 | blk.30.ffn_down_exps.weight | 0x1e34ea6e0 | 0x6c00000 |
| 371 | blk.30.ffn_gate_exps.weight | 0x1ea0ea6e0 | 0x5280000 |
| 372 | blk.30.ffn_gate_inp.weight | 0x1ef36a6e0 | 0x100000 |
| 373 | blk.30.ffn_norm.weight | 0x1ef46a6e0 | 0x2000 |
| 374 | blk.30.ffn_up_exps.weight | 0x1ef46c6e0 | 0x5280000 |
| 375 | blk.31.attn_k.weight | 0x1f46ec6e0 | 0x6e000 |
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| 377 | blk.31.attn_norm.weight | 0x1f475a8e0 | 0x2000 |
| 378 | blk.31.attn_output.weight | 0x1f475c8e0 | 0x370000 |
| 379 | blk.31.attn_q.weight | 0x1f4acc8e0 | 0x370000 |
| 380 | blk.31.attn_q_norm.weight | 0x1f4e3c8e0 | 0x200 |
| 381 | blk.31.attn_v.weight | 0x1f4e3cae0 | 0x6e000 |
| 382 | blk.31.ffn_down_exps.weight | 0x1f4eaaae0 | 0x6c00000 |
| 383 | blk.31.ffn_gate_exps.weight | 0x1fbaaaae0 | 0x5280000 |
| 384 | blk.31.ffn_gate_inp.weight | 0x200d2aae0 | 0x100000 |
| 385 | blk.31.ffn_norm.weight | 0x200e2aae0 | 0x2000 |
| 386 | blk.31.ffn_up_exps.weight | 0x200e2cae0 | 0x5280000 |
| 387 | blk.32.attn_k.weight | 0x2060acae0 | 0x6e000 |
| 388 | blk.32.attn_k_norm.weight | 0x20611aae0 | 0x200 |
| 389 | blk.32.attn_norm.weight | 0x20611ace0 | 0x2000 |
| 390 | blk.32.attn_output.weight | 0x20611cce0 | 0x370000 |
| 391 | blk.32.attn_q.weight | 0x20648cce0 | 0x370000 |
| 392 | blk.32.attn_q_norm.weight | 0x2067fcce0 | 0x200 |
| 393 | blk.32.attn_v.weight | 0x2067fcee0 | 0x6e000 |
| 394 | blk.32.ffn_down_exps.weight | 0x20686aee0 | 0x6c00000 |
| 395 | blk.32.ffn_gate_exps.weight | 0x20d46aee0 | 0x5280000 |
| 396 | blk.32.ffn_gate_inp.weight | 0x2126eaee0 | 0x100000 |
| 397 | blk.32.ffn_norm.weight | 0x2127eaee0 | 0x2000 |
| 398 | blk.32.ffn_up_exps.weight | 0x2127ecee0 | 0x5280000 |
| 399 | blk.33.attn_k.weight | 0x217a6cee0 | 0x6e000 |
| 400 | blk.33.attn_k_norm.weight | 0x217adaee0 | 0x200 |
| 401 | blk.33.attn_norm.weight | 0x217adb0e0 | 0x2000 |
| 402 | blk.33.attn_output.weight | 0x217add0e0 | 0x370000 |
| 403 | blk.33.attn_q.weight | 0x217e4d0e0 | 0x370000 |
| 404 | blk.33.attn_q_norm.weight | 0x2181bd0e0 | 0x200 |
| 405 | blk.33.attn_v.weight | 0x2181bd2e0 | 0x6e000 |
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| 407 | blk.33.ffn_gate_exps.weight | 0x21ee2b2e0 | 0x5280000 |
| 408 | blk.33.ffn_gate_inp.weight | 0x2240ab2e0 | 0x100000 |
| 409 | blk.33.ffn_norm.weight | 0x2241ab2e0 | 0x2000 |
| 410 | blk.33.ffn_up_exps.weight | 0x2241ad2e0 | 0x5280000 |
| 411 | blk.34.attn_k.weight | 0x22942d2e0 | 0x6e000 |
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| 413 | blk.34.attn_norm.weight | 0x22949b4e0 | 0x2000 |
| 414 | blk.34.attn_output.weight | 0x22949d4e0 | 0x370000 |
| 415 | blk.34.attn_q.weight | 0x22980d4e0 | 0x370000 |
| 416 | blk.34.attn_q_norm.weight | 0x229b7d4e0 | 0x200 |
| 417 | blk.34.attn_v.weight | 0x229b7d6e0 | 0x6e000 |
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| 419 | blk.34.ffn_gate_exps.weight | 0x2307eb6e0 | 0x5280000 |
| 420 | blk.34.ffn_gate_inp.weight | 0x235a6b6e0 | 0x100000 |
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| 422 | blk.34.ffn_up_exps.weight | 0x235b6d6e0 | 0x5280000 |
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| 425 | blk.35.attn_norm.weight | 0x23ae5b8e0 | 0x2000 |
| 426 | blk.35.attn_output.weight | 0x23ae5d8e0 | 0x370000 |
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| 428 | blk.35.attn_q_norm.weight | 0x23b53d8e0 | 0x200 |
| 429 | blk.35.attn_v.weight | 0x23b53dae0 | 0x6e000 |
| 430 | blk.35.ffn_down_exps.weight | 0x23b5abae0 | 0x6c00000 |
| 431 | blk.35.ffn_gate_exps.weight | 0x2421abae0 | 0x5280000 |
| 432 | blk.35.ffn_gate_inp.weight | 0x24742bae0 | 0x100000 |
| 433 | blk.35.ffn_norm.weight | 0x24752bae0 | 0x2000 |
| 434 | blk.35.ffn_up_exps.weight | 0x24752dae0 | 0x5280000 |
| 435 | blk.36.attn_k.weight | 0x24c7adae0 | 0x6e000 |
| 436 | blk.36.attn_k_norm.weight | 0x24c81bae0 | 0x200 |
| 437 | blk.36.attn_norm.weight | 0x24c81bce0 | 0x2000 |
| 438 | blk.36.attn_output.weight | 0x24c81dce0 | 0x370000 |
| 439 | blk.36.attn_q.weight | 0x24cb8dce0 | 0x370000 |
| 440 | blk.36.attn_q_norm.weight | 0x24cefdce0 | 0x200 |
| 441 | blk.36.attn_v.weight | 0x24cefdee0 | 0x6e000 |
| 442 | blk.36.ffn_down_exps.weight | 0x24cf6bee0 | 0x6c00000 |
| 443 | blk.36.ffn_gate_exps.weight | 0x253b6bee0 | 0x5280000 |
| 444 | blk.36.ffn_gate_inp.weight | 0x258debee0 | 0x100000 |
| 445 | blk.36.ffn_norm.weight | 0x258eebee0 | 0x2000 |
| 446 | blk.36.ffn_up_exps.weight | 0x258eedee0 | 0x5280000 |
| 447 | blk.37.attn_k.weight | 0x25e16dee0 | 0x6e000 |
| 448 | blk.37.attn_k_norm.weight | 0x25e1dbee0 | 0x200 |
| 449 | blk.37.attn_norm.weight | 0x25e1dc0e0 | 0x2000 |
| 450 | blk.37.attn_output.weight | 0x25e1de0e0 | 0x370000 |
| 451 | blk.37.attn_q.weight | 0x25e54e0e0 | 0x370000 |
| 452 | blk.37.attn_q_norm.weight | 0x25e8be0e0 | 0x200 |
| 453 | blk.37.attn_v.weight | 0x25e8be2e0 | 0x6e000 |
| 454 | blk.37.ffn_down_exps.weight | 0x25e92c2e0 | 0x6c00000 |
| 455 | blk.37.ffn_gate_exps.weight | 0x26552c2e0 | 0x5280000 |
| 456 | blk.37.ffn_gate_inp.weight | 0x26a7ac2e0 | 0x100000 |
| 457 | blk.37.ffn_norm.weight | 0x26a8ac2e0 | 0x2000 |
| 458 | blk.37.ffn_up_exps.weight | 0x26a8ae2e0 | 0x5280000 |
| 459 | blk.38.attn_k.weight | 0x26fb2e2e0 | 0x6e000 |
| 460 | blk.38.attn_k_norm.weight | 0x26fb9c2e0 | 0x200 |
| 461 | blk.38.attn_norm.weight | 0x26fb9c4e0 | 0x2000 |
| 462 | blk.38.attn_output.weight | 0x26fb9e4e0 | 0x370000 |
| 463 | blk.38.attn_q.weight | 0x26ff0e4e0 | 0x370000 |
| 464 | blk.38.attn_q_norm.weight | 0x27027e4e0 | 0x200 |
| 465 | blk.38.attn_v.weight | 0x27027e6e0 | 0x6e000 |
| 466 | blk.38.ffn_down_exps.weight | 0x2702ec6e0 | 0x6c00000 |
| 467 | blk.38.ffn_gate_exps.weight | 0x276eec6e0 | 0x5280000 |
| 468 | blk.38.ffn_gate_inp.weight | 0x27c16c6e0 | 0x100000 |
| 469 | blk.38.ffn_norm.weight | 0x27c26c6e0 | 0x2000 |
| 470 | blk.38.ffn_up_exps.weight | 0x27c26e6e0 | 0x5280000 |
| 471 | blk.39.attn_k.weight | 0x2814ee6e0 | 0x6e000 |
| 472 | blk.39.attn_k_norm.weight | 0x28155c6e0 | 0x200 |
| 473 | blk.39.attn_norm.weight | 0x28155c8e0 | 0x2000 |
| 474 | blk.39.attn_output.weight | 0x28155e8e0 | 0x370000 |
| 475 | blk.39.attn_q.weight | 0x2818ce8e0 | 0x370000 |
| 476 | blk.39.attn_q_norm.weight | 0x281c3e8e0 | 0x200 |
| 477 | blk.39.attn_v.weight | 0x281c3eae0 | 0x6e000 |
| 478 | blk.39.ffn_down_exps.weight | 0x281cacae0 | 0x6c00000 |
| 479 | blk.39.ffn_gate_exps.weight | 0x2888acae0 | 0x5280000 |
| 480 | blk.39.ffn_gate_inp.weight | 0x28db2cae0 | 0x100000 |
| 481 | blk.39.ffn_norm.weight | 0x28dc2cae0 | 0x2000 |
| 482 | blk.39.ffn_up_exps.weight | 0x28dc2eae0 | 0x5280000 |
| 483 | blk.40.attn_k.weight | 0x292eaeae0 | 0x6e000 |
| 484 | blk.40.attn_k_norm.weight | 0x292f1cae0 | 0x200 |
| 485 | blk.40.attn_norm.weight | 0x292f1cce0 | 0x2000 |
| 486 | blk.40.attn_output.weight | 0x292f1ece0 | 0x370000 |
| 487 | blk.40.attn_q.weight | 0x29328ece0 | 0x370000 |
| 488 | blk.40.attn_q_norm.weight | 0x2935fece0 | 0x200 |
| 489 | blk.40.attn_v.weight | 0x2935feee0 | 0x6e000 |
| 490 | blk.40.ffn_down_exps.weight | 0x29366cee0 | 0x6c00000 |
| 491 | blk.40.ffn_gate_exps.weight | 0x29a26cee0 | 0x5280000 |
| 492 | blk.40.ffn_gate_inp.weight | 0x29f4ecee0 | 0x100000 |
| 493 | blk.40.ffn_norm.weight | 0x29f5ecee0 | 0x2000 |
| 494 | blk.40.ffn_up_exps.weight | 0x29f5eeee0 | 0x5280000 |
| 495 | blk.41.attn_k.weight | 0x2a486eee0 | 0x6e000 |
| 496 | blk.41.attn_k_norm.weight | 0x2a48dcee0 | 0x200 |
| 497 | blk.41.attn_norm.weight | 0x2a48dd0e0 | 0x2000 |
| 498 | blk.41.attn_output.weight | 0x2a48df0e0 | 0x370000 |
| 499 | blk.41.attn_q.weight | 0x2a4c4f0e0 | 0x370000 |
| 500 | blk.41.attn_q_norm.weight | 0x2a4fbf0e0 | 0x200 |
| 501 | blk.41.attn_v.weight | 0x2a4fbf2e0 | 0x6e000 |
| 502 | blk.41.ffn_down_exps.weight | 0x2a502d2e0 | 0x6c00000 |
| 503 | blk.41.ffn_gate_exps.weight | 0x2abc2d2e0 | 0x5280000 |
| 504 | blk.41.ffn_gate_inp.weight | 0x2b0ead2e0 | 0x100000 |
| 505 | blk.41.ffn_norm.weight | 0x2b0fad2e0 | 0x2000 |
| 506 | blk.41.ffn_up_exps.weight | 0x2b0faf2e0 | 0x5280000 |
| 507 | blk.42.attn_k.weight | 0x2b622f2e0 | 0x6e000 |
| 508 | blk.42.attn_k_norm.weight | 0x2b629d2e0 | 0x200 |
| 509 | blk.42.attn_norm.weight | 0x2b629d4e0 | 0x2000 |
| 510 | blk.42.attn_output.weight | 0x2b629f4e0 | 0x370000 |
| 511 | blk.42.attn_q.weight | 0x2b660f4e0 | 0x370000 |
| 512 | blk.42.attn_q_norm.weight | 0x2b697f4e0 | 0x200 |
| 513 | blk.42.attn_v.weight | 0x2b697f6e0 | 0x6e000 |
| 514 | blk.42.ffn_down_exps.weight | 0x2b69ed6e0 | 0x6c00000 |
| 515 | blk.42.ffn_gate_exps.weight | 0x2bd5ed6e0 | 0x5280000 |
| 516 | blk.42.ffn_gate_inp.weight | 0x2c286d6e0 | 0x100000 |
| 517 | blk.42.ffn_norm.weight | 0x2c296d6e0 | 0x2000 |
| 518 | blk.42.ffn_up_exps.weight | 0x2c296f6e0 | 0x5280000 |
| 519 | blk.43.attn_k.weight | 0x2c7bef6e0 | 0x6e000 |
| 520 | blk.43.attn_k_norm.weight | 0x2c7c5d6e0 | 0x200 |
| 521 | blk.43.attn_norm.weight | 0x2c7c5d8e0 | 0x2000 |
| 522 | blk.43.attn_output.weight | 0x2c7c5f8e0 | 0x370000 |
| 523 | blk.43.attn_q.weight | 0x2c7fcf8e0 | 0x370000 |
| 524 | blk.43.attn_q_norm.weight | 0x2c833f8e0 | 0x200 |
| 525 | blk.43.attn_v.weight | 0x2c833fae0 | 0x6e000 |
| 526 | blk.43.ffn_down_exps.weight | 0x2c83adae0 | 0x6c00000 |
| 527 | blk.43.ffn_gate_exps.weight | 0x2cefadae0 | 0x5280000 |
| 528 | blk.43.ffn_gate_inp.weight | 0x2d422dae0 | 0x100000 |
| 529 | blk.43.ffn_norm.weight | 0x2d432dae0 | 0x2000 |
| 530 | blk.43.ffn_up_exps.weight | 0x2d432fae0 | 0x5280000 |
| 531 | blk.44.attn_k.weight | 0x2d95afae0 | 0x6e000 |
| 532 | blk.44.attn_k_norm.weight | 0x2d961dae0 | 0x200 |
| 533 | blk.44.attn_norm.weight | 0x2d961dce0 | 0x2000 |
| 534 | blk.44.attn_output.weight | 0x2d961fce0 | 0x370000 |
| 535 | blk.44.attn_q.weight | 0x2d998fce0 | 0x370000 |
| 536 | blk.44.attn_q_norm.weight | 0x2d9cffce0 | 0x200 |
| 537 | blk.44.attn_v.weight | 0x2d9cffee0 | 0x6e000 |
| 538 | blk.44.ffn_down_exps.weight | 0x2d9d6dee0 | 0x6c00000 |
| 539 | blk.44.ffn_gate_exps.weight | 0x2e096dee0 | 0x5280000 |
| 540 | blk.44.ffn_gate_inp.weight | 0x2e5bedee0 | 0x100000 |
| 541 | blk.44.ffn_norm.weight | 0x2e5cedee0 | 0x2000 |
| 542 | blk.44.ffn_up_exps.weight | 0x2e5cefee0 | 0x5280000 |
| 543 | blk.45.attn_k.weight | 0x2eaf6fee0 | 0x6e000 |
| 544 | blk.45.attn_k_norm.weight | 0x2eafddee0 | 0x200 |
| 545 | blk.45.attn_norm.weight | 0x2eafde0e0 | 0x2000 |
| 546 | blk.45.attn_output.weight | 0x2eafe00e0 | 0x370000 |
| 547 | blk.45.attn_q.weight | 0x2eb3500e0 | 0x370000 |
| 548 | blk.45.attn_q_norm.weight | 0x2eb6c00e0 | 0x200 |
| 549 | blk.45.attn_v.weight | 0x2eb6c02e0 | 0x6e000 |
| 550 | blk.45.ffn_down_exps.weight | 0x2eb72e2e0 | 0x6c00000 |
| 551 | blk.45.ffn_gate_exps.weight | 0x2f232e2e0 | 0x5280000 |
| 552 | blk.45.ffn_gate_inp.weight | 0x2f75ae2e0 | 0x100000 |
| 553 | blk.45.ffn_norm.weight | 0x2f76ae2e0 | 0x2000 |
| 554 | blk.45.ffn_up_exps.weight | 0x2f76b02e0 | 0x5280000 |
Base Tensor Group : ~622M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 0 | output.weight | Output (W) | (~311M) 311164928 | 2048 x 151936 x 1 x 1 | Q3_K |
| 1 | output_norm.weight | Output Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 2 | token_embd.weight | Token Embedding (W) | (~311M) 311164928 | 2048 x 151936 x 1 x 1 | Q2_K |
- Total elements in base: (~622M) 622331904
- Percentage of total elements: 2.13%
Block 0 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 3 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 4 | blk.0.attn_k_norm.weight | Block 0 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 5 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 6 | blk.0.attn_output.weight | Block 0 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 7 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 8 | blk.0.attn_q_norm.weight | Block 0 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 9 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 10 | blk.0.ffn_down_exps.weight | Block 0 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 11 | blk.0.ffn_gate_exps.weight | Block 0 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 12 | blk.0.ffn_gate_inp.weight | Block 0 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 13 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 14 | blk.0.ffn_up_exps.weight | Block 0 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.0: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 1 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 15 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 16 | blk.1.attn_k_norm.weight | Block 1 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 17 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 18 | blk.1.attn_output.weight | Block 1 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 19 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 20 | blk.1.attn_q_norm.weight | Block 1 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 21 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 22 | blk.1.ffn_down_exps.weight | Block 1 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 23 | blk.1.ffn_gate_exps.weight | Block 1 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 24 | blk.1.ffn_gate_inp.weight | Block 1 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 25 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 26 | blk.1.ffn_up_exps.weight | Block 1 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.1: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 2 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 27 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 28 | blk.2.attn_k_norm.weight | Block 2 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 29 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 30 | blk.2.attn_output.weight | Block 2 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 31 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 32 | blk.2.attn_q_norm.weight | Block 2 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 33 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 34 | blk.2.ffn_down_exps.weight | Block 2 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 35 | blk.2.ffn_gate_exps.weight | Block 2 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 36 | blk.2.ffn_gate_inp.weight | Block 2 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 37 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 38 | blk.2.ffn_up_exps.weight | Block 2 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.2: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 3 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 39 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 40 | blk.3.attn_k_norm.weight | Block 3 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 41 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 42 | blk.3.attn_output.weight | Block 3 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 43 | blk.3.attn_q.weight | Block 3 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 44 | blk.3.attn_q_norm.weight | Block 3 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 45 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 46 | blk.3.ffn_down_exps.weight | Block 3 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 47 | blk.3.ffn_gate_exps.weight | Block 3 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 48 | blk.3.ffn_gate_inp.weight | Block 3 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 49 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 50 | blk.3.ffn_up_exps.weight | Block 3 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.3: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 4 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 51 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 52 | blk.4.attn_k_norm.weight | Block 4 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 53 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 54 | blk.4.attn_output.weight | Block 4 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 55 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 56 | blk.4.attn_q_norm.weight | Block 4 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 57 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 58 | blk.4.ffn_down_exps.weight | Block 4 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 59 | blk.4.ffn_gate_exps.weight | Block 4 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 60 | blk.4.ffn_gate_inp.weight | Block 4 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 61 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 62 | blk.4.ffn_up_exps.weight | Block 4 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.4: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 5 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 63 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 64 | blk.5.attn_k_norm.weight | Block 5 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 65 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 66 | blk.5.attn_output.weight | Block 5 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 67 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 68 | blk.5.attn_q_norm.weight | Block 5 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 69 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 70 | blk.5.ffn_down_exps.weight | Block 5 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 71 | blk.5.ffn_gate_exps.weight | Block 5 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 72 | blk.5.ffn_gate_inp.weight | Block 5 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 73 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 74 | blk.5.ffn_up_exps.weight | Block 5 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.5: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 6 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 75 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 76 | blk.6.attn_k_norm.weight | Block 6 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 77 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 78 | blk.6.attn_output.weight | Block 6 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 79 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 80 | blk.6.attn_q_norm.weight | Block 6 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 81 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 82 | blk.6.ffn_down_exps.weight | Block 6 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 83 | blk.6.ffn_gate_exps.weight | Block 6 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 84 | blk.6.ffn_gate_inp.weight | Block 6 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 85 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 86 | blk.6.ffn_up_exps.weight | Block 6 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.6: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 7 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 87 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 88 | blk.7.attn_k_norm.weight | Block 7 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 89 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 90 | blk.7.attn_output.weight | Block 7 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 91 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 92 | blk.7.attn_q_norm.weight | Block 7 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 93 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 94 | blk.7.ffn_down_exps.weight | Block 7 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 95 | blk.7.ffn_gate_exps.weight | Block 7 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 96 | blk.7.ffn_gate_inp.weight | Block 7 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 97 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 98 | blk.7.ffn_up_exps.weight | Block 7 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.7: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 8 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 99 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 100 | blk.8.attn_k_norm.weight | Block 8 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 101 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 102 | blk.8.attn_output.weight | Block 8 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 103 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 104 | blk.8.attn_q_norm.weight | Block 8 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 105 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 106 | blk.8.ffn_down_exps.weight | Block 8 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 107 | blk.8.ffn_gate_exps.weight | Block 8 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 108 | blk.8.ffn_gate_inp.weight | Block 8 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 109 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 110 | blk.8.ffn_up_exps.weight | Block 8 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.8: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 9 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 111 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 112 | blk.9.attn_k_norm.weight | Block 9 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 113 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 114 | blk.9.attn_output.weight | Block 9 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 115 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 116 | blk.9.attn_q_norm.weight | Block 9 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 117 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 118 | blk.9.ffn_down_exps.weight | Block 9 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 119 | blk.9.ffn_gate_exps.weight | Block 9 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 120 | blk.9.ffn_gate_inp.weight | Block 9 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 121 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 122 | blk.9.ffn_up_exps.weight | Block 9 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.9: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 10 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 123 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 124 | blk.10.attn_k_norm.weight | Block 10 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 125 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 126 | blk.10.attn_output.weight | Block 10 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 127 | blk.10.attn_q.weight | Block 10 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 128 | blk.10.attn_q_norm.weight | Block 10 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 129 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 130 | blk.10.ffn_down_exps.weight | Block 10 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 131 | blk.10.ffn_gate_exps.weight | Block 10 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 132 | blk.10.ffn_gate_inp.weight | Block 10 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 133 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 134 | blk.10.ffn_up_exps.weight | Block 10 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.10: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 11 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 135 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 136 | blk.11.attn_k_norm.weight | Block 11 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 137 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 138 | blk.11.attn_output.weight | Block 11 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 139 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 140 | blk.11.attn_q_norm.weight | Block 11 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 141 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 142 | blk.11.ffn_down_exps.weight | Block 11 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 143 | blk.11.ffn_gate_exps.weight | Block 11 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 144 | blk.11.ffn_gate_inp.weight | Block 11 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 145 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 146 | blk.11.ffn_up_exps.weight | Block 11 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.11: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 12 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 147 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 148 | blk.12.attn_k_norm.weight | Block 12 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 149 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 150 | blk.12.attn_output.weight | Block 12 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 151 | blk.12.attn_q.weight | Block 12 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 152 | blk.12.attn_q_norm.weight | Block 12 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 153 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 154 | blk.12.ffn_down_exps.weight | Block 12 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 155 | blk.12.ffn_gate_exps.weight | Block 12 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 156 | blk.12.ffn_gate_inp.weight | Block 12 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 157 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 158 | blk.12.ffn_up_exps.weight | Block 12 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.12: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 13 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 159 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 160 | blk.13.attn_k_norm.weight | Block 13 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 161 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 162 | blk.13.attn_output.weight | Block 13 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 163 | blk.13.attn_q.weight | Block 13 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 164 | blk.13.attn_q_norm.weight | Block 13 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 165 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 166 | blk.13.ffn_down_exps.weight | Block 13 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 167 | blk.13.ffn_gate_exps.weight | Block 13 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 168 | blk.13.ffn_gate_inp.weight | Block 13 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 169 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 170 | blk.13.ffn_up_exps.weight | Block 13 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.13: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 14 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 171 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 172 | blk.14.attn_k_norm.weight | Block 14 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 173 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 174 | blk.14.attn_output.weight | Block 14 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 175 | blk.14.attn_q.weight | Block 14 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 176 | blk.14.attn_q_norm.weight | Block 14 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 177 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 178 | blk.14.ffn_down_exps.weight | Block 14 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 179 | blk.14.ffn_gate_exps.weight | Block 14 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 180 | blk.14.ffn_gate_inp.weight | Block 14 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 181 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 182 | blk.14.ffn_up_exps.weight | Block 14 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.14: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 15 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 183 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 184 | blk.15.attn_k_norm.weight | Block 15 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 185 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 186 | blk.15.attn_output.weight | Block 15 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 187 | blk.15.attn_q.weight | Block 15 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 188 | blk.15.attn_q_norm.weight | Block 15 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 189 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 190 | blk.15.ffn_down_exps.weight | Block 15 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 191 | blk.15.ffn_gate_exps.weight | Block 15 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 192 | blk.15.ffn_gate_inp.weight | Block 15 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 193 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 194 | blk.15.ffn_up_exps.weight | Block 15 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.15: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 16 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 195 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 196 | blk.16.attn_k_norm.weight | Block 16 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 197 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 198 | blk.16.attn_output.weight | Block 16 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 199 | blk.16.attn_q.weight | Block 16 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 200 | blk.16.attn_q_norm.weight | Block 16 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 201 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 202 | blk.16.ffn_down_exps.weight | Block 16 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 203 | blk.16.ffn_gate_exps.weight | Block 16 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 204 | blk.16.ffn_gate_inp.weight | Block 16 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 205 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 206 | blk.16.ffn_up_exps.weight | Block 16 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.16: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 17 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 207 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 208 | blk.17.attn_k_norm.weight | Block 17 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 209 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 210 | blk.17.attn_output.weight | Block 17 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 211 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 212 | blk.17.attn_q_norm.weight | Block 17 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 213 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 214 | blk.17.ffn_down_exps.weight | Block 17 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 215 | blk.17.ffn_gate_exps.weight | Block 17 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 216 | blk.17.ffn_gate_inp.weight | Block 17 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 217 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 218 | blk.17.ffn_up_exps.weight | Block 17 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.17: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 18 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 219 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 220 | blk.18.attn_k_norm.weight | Block 18 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 221 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 222 | blk.18.attn_output.weight | Block 18 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 223 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 224 | blk.18.attn_q_norm.weight | Block 18 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 225 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 226 | blk.18.ffn_down_exps.weight | Block 18 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 227 | blk.18.ffn_gate_exps.weight | Block 18 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 228 | blk.18.ffn_gate_inp.weight | Block 18 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 229 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 230 | blk.18.ffn_up_exps.weight | Block 18 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.18: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 19 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 231 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 232 | blk.19.attn_k_norm.weight | Block 19 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 233 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 234 | blk.19.attn_output.weight | Block 19 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 235 | blk.19.attn_q.weight | Block 19 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 236 | blk.19.attn_q_norm.weight | Block 19 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 237 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 238 | blk.19.ffn_down_exps.weight | Block 19 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 239 | blk.19.ffn_gate_exps.weight | Block 19 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 240 | blk.19.ffn_gate_inp.weight | Block 19 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 241 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 242 | blk.19.ffn_up_exps.weight | Block 19 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.19: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 20 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 243 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 244 | blk.20.attn_k_norm.weight | Block 20 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 245 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 246 | blk.20.attn_output.weight | Block 20 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 247 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 248 | blk.20.attn_q_norm.weight | Block 20 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 249 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 250 | blk.20.ffn_down_exps.weight | Block 20 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 251 | blk.20.ffn_gate_exps.weight | Block 20 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 252 | blk.20.ffn_gate_inp.weight | Block 20 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 253 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 254 | blk.20.ffn_up_exps.weight | Block 20 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.20: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 21 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 255 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 256 | blk.21.attn_k_norm.weight | Block 21 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 257 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 258 | blk.21.attn_output.weight | Block 21 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 259 | blk.21.attn_q.weight | Block 21 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 260 | blk.21.attn_q_norm.weight | Block 21 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 261 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 262 | blk.21.ffn_down_exps.weight | Block 21 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 263 | blk.21.ffn_gate_exps.weight | Block 21 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 264 | blk.21.ffn_gate_inp.weight | Block 21 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 265 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 266 | blk.21.ffn_up_exps.weight | Block 21 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.21: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 22 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 267 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 268 | blk.22.attn_k_norm.weight | Block 22 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 269 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 270 | blk.22.attn_output.weight | Block 22 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 271 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 272 | blk.22.attn_q_norm.weight | Block 22 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 273 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 274 | blk.22.ffn_down_exps.weight | Block 22 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 275 | blk.22.ffn_gate_exps.weight | Block 22 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 276 | blk.22.ffn_gate_inp.weight | Block 22 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 277 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 278 | blk.22.ffn_up_exps.weight | Block 22 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.22: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 23 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 279 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q2_K |
| 280 | blk.23.attn_k_norm.weight | Block 23 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 281 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 282 | blk.23.attn_output.weight | Block 23 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 283 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q2_K |
| 284 | blk.23.attn_q_norm.weight | Block 23 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 285 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 286 | blk.23.ffn_down_exps.weight | Block 23 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 287 | blk.23.ffn_gate_exps.weight | Block 23 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 288 | blk.23.ffn_gate_inp.weight | Block 23 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 289 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 290 | blk.23.ffn_up_exps.weight | Block 23 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.23: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 24 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 291 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 292 | blk.24.attn_k_norm.weight | Block 24 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 293 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 294 | blk.24.attn_output.weight | Block 24 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 295 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 296 | blk.24.attn_q_norm.weight | Block 24 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 297 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 298 | blk.24.ffn_down_exps.weight | Block 24 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 299 | blk.24.ffn_gate_exps.weight | Block 24 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
| 300 | blk.24.ffn_gate_inp.weight | Block 24 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 301 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 302 | blk.24.ffn_up_exps.weight | Block 24 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q2_K |
- Total elements in blk.24: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 25 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 303 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 304 | blk.25.attn_k_norm.weight | Block 25 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 305 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 306 | blk.25.attn_output.weight | Block 25 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 307 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 308 | blk.25.attn_q_norm.weight | Block 25 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 309 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 310 | blk.25.ffn_down_exps.weight | Block 25 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 311 | blk.25.ffn_gate_exps.weight | Block 25 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 312 | blk.25.ffn_gate_inp.weight | Block 25 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 313 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 314 | blk.25.ffn_up_exps.weight | Block 25 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.25: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 26 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 315 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 316 | blk.26.attn_k_norm.weight | Block 26 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 317 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 318 | blk.26.attn_output.weight | Block 26 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 319 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 320 | blk.26.attn_q_norm.weight | Block 26 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 321 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 322 | blk.26.ffn_down_exps.weight | Block 26 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 323 | blk.26.ffn_gate_exps.weight | Block 26 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 324 | blk.26.ffn_gate_inp.weight | Block 26 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 325 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 326 | blk.26.ffn_up_exps.weight | Block 26 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.26: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 27 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 327 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 328 | blk.27.attn_k_norm.weight | Block 27 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 329 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 330 | blk.27.attn_output.weight | Block 27 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 331 | blk.27.attn_q.weight | Block 27 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 332 | blk.27.attn_q_norm.weight | Block 27 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 333 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 334 | blk.27.ffn_down_exps.weight | Block 27 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 335 | blk.27.ffn_gate_exps.weight | Block 27 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 336 | blk.27.ffn_gate_inp.weight | Block 27 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 337 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 338 | blk.27.ffn_up_exps.weight | Block 27 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.27: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 28 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 339 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 340 | blk.28.attn_k_norm.weight | Block 28 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 341 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 342 | blk.28.attn_output.weight | Block 28 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 343 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 344 | blk.28.attn_q_norm.weight | Block 28 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 345 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 346 | blk.28.ffn_down_exps.weight | Block 28 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 347 | blk.28.ffn_gate_exps.weight | Block 28 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 348 | blk.28.ffn_gate_inp.weight | Block 28 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 349 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 350 | blk.28.ffn_up_exps.weight | Block 28 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.28: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 29 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 351 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 352 | blk.29.attn_k_norm.weight | Block 29 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 353 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 354 | blk.29.attn_output.weight | Block 29 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 355 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 356 | blk.29.attn_q_norm.weight | Block 29 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 357 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 358 | blk.29.ffn_down_exps.weight | Block 29 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 359 | blk.29.ffn_gate_exps.weight | Block 29 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 360 | blk.29.ffn_gate_inp.weight | Block 29 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 361 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 362 | blk.29.ffn_up_exps.weight | Block 29 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.29: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 30 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 363 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 364 | blk.30.attn_k_norm.weight | Block 30 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 365 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 366 | blk.30.attn_output.weight | Block 30 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 367 | blk.30.attn_q.weight | Block 30 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 368 | blk.30.attn_q_norm.weight | Block 30 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 369 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 370 | blk.30.ffn_down_exps.weight | Block 30 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 371 | blk.30.ffn_gate_exps.weight | Block 30 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 372 | blk.30.ffn_gate_inp.weight | Block 30 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 373 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 374 | blk.30.ffn_up_exps.weight | Block 30 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.30: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 31 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 375 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 376 | blk.31.attn_k_norm.weight | Block 31 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 377 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 378 | blk.31.attn_output.weight | Block 31 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 379 | blk.31.attn_q.weight | Block 31 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 380 | blk.31.attn_q_norm.weight | Block 31 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 381 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 382 | blk.31.ffn_down_exps.weight | Block 31 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 383 | blk.31.ffn_gate_exps.weight | Block 31 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 384 | blk.31.ffn_gate_inp.weight | Block 31 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 385 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 386 | blk.31.ffn_up_exps.weight | Block 31 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.31: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 32 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 387 | blk.32.attn_k.weight | Block 32 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 388 | blk.32.attn_k_norm.weight | Block 32 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 389 | blk.32.attn_norm.weight | Block 32 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 390 | blk.32.attn_output.weight | Block 32 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 391 | blk.32.attn_q.weight | Block 32 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 392 | blk.32.attn_q_norm.weight | Block 32 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 393 | blk.32.attn_v.weight | Block 32 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 394 | blk.32.ffn_down_exps.weight | Block 32 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 395 | blk.32.ffn_gate_exps.weight | Block 32 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 396 | blk.32.ffn_gate_inp.weight | Block 32 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 397 | blk.32.ffn_norm.weight | Block 32 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 398 | blk.32.ffn_up_exps.weight | Block 32 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.32: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 33 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 399 | blk.33.attn_k.weight | Block 33 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 400 | blk.33.attn_k_norm.weight | Block 33 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 401 | blk.33.attn_norm.weight | Block 33 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 402 | blk.33.attn_output.weight | Block 33 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 403 | blk.33.attn_q.weight | Block 33 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 404 | blk.33.attn_q_norm.weight | Block 33 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 405 | blk.33.attn_v.weight | Block 33 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 406 | blk.33.ffn_down_exps.weight | Block 33 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 407 | blk.33.ffn_gate_exps.weight | Block 33 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 408 | blk.33.ffn_gate_inp.weight | Block 33 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 409 | blk.33.ffn_norm.weight | Block 33 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 410 | blk.33.ffn_up_exps.weight | Block 33 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.33: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 34 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 411 | blk.34.attn_k.weight | Block 34 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 412 | blk.34.attn_k_norm.weight | Block 34 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 413 | blk.34.attn_norm.weight | Block 34 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 414 | blk.34.attn_output.weight | Block 34 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 415 | blk.34.attn_q.weight | Block 34 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 416 | blk.34.attn_q_norm.weight | Block 34 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 417 | blk.34.attn_v.weight | Block 34 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 418 | blk.34.ffn_down_exps.weight | Block 34 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 419 | blk.34.ffn_gate_exps.weight | Block 34 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 420 | blk.34.ffn_gate_inp.weight | Block 34 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 421 | blk.34.ffn_norm.weight | Block 34 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 422 | blk.34.ffn_up_exps.weight | Block 34 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.34: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 35 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 423 | blk.35.attn_k.weight | Block 35 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 424 | blk.35.attn_k_norm.weight | Block 35 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 425 | blk.35.attn_norm.weight | Block 35 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 426 | blk.35.attn_output.weight | Block 35 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 427 | blk.35.attn_q.weight | Block 35 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 428 | blk.35.attn_q_norm.weight | Block 35 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 429 | blk.35.attn_v.weight | Block 35 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 430 | blk.35.ffn_down_exps.weight | Block 35 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 431 | blk.35.ffn_gate_exps.weight | Block 35 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 432 | blk.35.ffn_gate_inp.weight | Block 35 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 433 | blk.35.ffn_norm.weight | Block 35 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 434 | blk.35.ffn_up_exps.weight | Block 35 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.35: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 36 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 435 | blk.36.attn_k.weight | Block 36 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 436 | blk.36.attn_k_norm.weight | Block 36 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 437 | blk.36.attn_norm.weight | Block 36 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 438 | blk.36.attn_output.weight | Block 36 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 439 | blk.36.attn_q.weight | Block 36 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 440 | blk.36.attn_q_norm.weight | Block 36 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 441 | blk.36.attn_v.weight | Block 36 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 442 | blk.36.ffn_down_exps.weight | Block 36 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 443 | blk.36.ffn_gate_exps.weight | Block 36 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 444 | blk.36.ffn_gate_inp.weight | Block 36 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 445 | blk.36.ffn_norm.weight | Block 36 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 446 | blk.36.ffn_up_exps.weight | Block 36 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.36: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 37 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 447 | blk.37.attn_k.weight | Block 37 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 448 | blk.37.attn_k_norm.weight | Block 37 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 449 | blk.37.attn_norm.weight | Block 37 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 450 | blk.37.attn_output.weight | Block 37 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 451 | blk.37.attn_q.weight | Block 37 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 452 | blk.37.attn_q_norm.weight | Block 37 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 453 | blk.37.attn_v.weight | Block 37 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 454 | blk.37.ffn_down_exps.weight | Block 37 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 455 | blk.37.ffn_gate_exps.weight | Block 37 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 456 | blk.37.ffn_gate_inp.weight | Block 37 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 457 | blk.37.ffn_norm.weight | Block 37 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 458 | blk.37.ffn_up_exps.weight | Block 37 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.37: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 38 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 459 | blk.38.attn_k.weight | Block 38 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 460 | blk.38.attn_k_norm.weight | Block 38 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 461 | blk.38.attn_norm.weight | Block 38 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 462 | blk.38.attn_output.weight | Block 38 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 463 | blk.38.attn_q.weight | Block 38 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 464 | blk.38.attn_q_norm.weight | Block 38 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 465 | blk.38.attn_v.weight | Block 38 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 466 | blk.38.ffn_down_exps.weight | Block 38 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 467 | blk.38.ffn_gate_exps.weight | Block 38 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 468 | blk.38.ffn_gate_inp.weight | Block 38 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 469 | blk.38.ffn_norm.weight | Block 38 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 470 | blk.38.ffn_up_exps.weight | Block 38 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.38: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 39 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 471 | blk.39.attn_k.weight | Block 39 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 472 | blk.39.attn_k_norm.weight | Block 39 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 473 | blk.39.attn_norm.weight | Block 39 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 474 | blk.39.attn_output.weight | Block 39 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 475 | blk.39.attn_q.weight | Block 39 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 476 | blk.39.attn_q_norm.weight | Block 39 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 477 | blk.39.attn_v.weight | Block 39 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 478 | blk.39.ffn_down_exps.weight | Block 39 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 479 | blk.39.ffn_gate_exps.weight | Block 39 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 480 | blk.39.ffn_gate_inp.weight | Block 39 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 481 | blk.39.ffn_norm.weight | Block 39 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 482 | blk.39.ffn_up_exps.weight | Block 39 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.39: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 40 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 483 | blk.40.attn_k.weight | Block 40 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 484 | blk.40.attn_k_norm.weight | Block 40 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 485 | blk.40.attn_norm.weight | Block 40 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 486 | blk.40.attn_output.weight | Block 40 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 487 | blk.40.attn_q.weight | Block 40 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 488 | blk.40.attn_q_norm.weight | Block 40 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 489 | blk.40.attn_v.weight | Block 40 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 490 | blk.40.ffn_down_exps.weight | Block 40 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 491 | blk.40.ffn_gate_exps.weight | Block 40 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 492 | blk.40.ffn_gate_inp.weight | Block 40 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 493 | blk.40.ffn_norm.weight | Block 40 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 494 | blk.40.ffn_up_exps.weight | Block 40 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.40: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 41 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 495 | blk.41.attn_k.weight | Block 41 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 496 | blk.41.attn_k_norm.weight | Block 41 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 497 | blk.41.attn_norm.weight | Block 41 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 498 | blk.41.attn_output.weight | Block 41 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 499 | blk.41.attn_q.weight | Block 41 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 500 | blk.41.attn_q_norm.weight | Block 41 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 501 | blk.41.attn_v.weight | Block 41 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 502 | blk.41.ffn_down_exps.weight | Block 41 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 503 | blk.41.ffn_gate_exps.weight | Block 41 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 504 | blk.41.ffn_gate_inp.weight | Block 41 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 505 | blk.41.ffn_norm.weight | Block 41 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 506 | blk.41.ffn_up_exps.weight | Block 41 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.41: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 42 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 507 | blk.42.attn_k.weight | Block 42 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 508 | blk.42.attn_k_norm.weight | Block 42 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 509 | blk.42.attn_norm.weight | Block 42 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 510 | blk.42.attn_output.weight | Block 42 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 511 | blk.42.attn_q.weight | Block 42 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 512 | blk.42.attn_q_norm.weight | Block 42 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 513 | blk.42.attn_v.weight | Block 42 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 514 | blk.42.ffn_down_exps.weight | Block 42 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 515 | blk.42.ffn_gate_exps.weight | Block 42 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 516 | blk.42.ffn_gate_inp.weight | Block 42 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 517 | blk.42.ffn_norm.weight | Block 42 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 518 | blk.42.ffn_up_exps.weight | Block 42 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.42: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 43 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 519 | blk.43.attn_k.weight | Block 43 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 520 | blk.43.attn_k_norm.weight | Block 43 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 521 | blk.43.attn_norm.weight | Block 43 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 522 | blk.43.attn_output.weight | Block 43 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 523 | blk.43.attn_q.weight | Block 43 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 524 | blk.43.attn_q_norm.weight | Block 43 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 525 | blk.43.attn_v.weight | Block 43 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 526 | blk.43.ffn_down_exps.weight | Block 43 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 527 | blk.43.ffn_gate_exps.weight | Block 43 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 528 | blk.43.ffn_gate_inp.weight | Block 43 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 529 | blk.43.ffn_norm.weight | Block 43 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 530 | blk.43.ffn_up_exps.weight | Block 43 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.43: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 44 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 531 | blk.44.attn_k.weight | Block 44 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 532 | blk.44.attn_k_norm.weight | Block 44 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 533 | blk.44.attn_norm.weight | Block 44 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 534 | blk.44.attn_output.weight | Block 44 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 535 | blk.44.attn_q.weight | Block 44 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 536 | blk.44.attn_q_norm.weight | Block 44 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 537 | blk.44.attn_v.weight | Block 44 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 538 | blk.44.ffn_down_exps.weight | Block 44 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 539 | blk.44.ffn_gate_exps.weight | Block 44 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 540 | blk.44.ffn_gate_inp.weight | Block 44 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 541 | blk.44.ffn_norm.weight | Block 44 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 542 | blk.44.ffn_up_exps.weight | Block 44 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.44: (~623M) 623120640
- Percentage of total elements: 2.13%
Block 45 Tensor Group : ~623M Elements
| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
|---|---|---|---|---|---|
| 543 | blk.45.attn_k.weight | Block 45 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 544 | blk.45.attn_k_norm.weight | Block 45 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 545 | blk.45.attn_norm.weight | Block 45 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 546 | blk.45.attn_output.weight | Block 45 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q3_K |
| 547 | blk.45.attn_q.weight | Block 45 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q3_K |
| 548 | blk.45.attn_q_norm.weight | Block 45 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
| 549 | blk.45.attn_v.weight | Block 45 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q3_K |
| 550 | blk.45.ffn_down_exps.weight | Block 45 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q4_K |
| 551 | blk.45.ffn_gate_exps.weight | Block 45 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
| 552 | blk.45.ffn_gate_inp.weight | Block 45 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
| 553 | blk.45.ffn_norm.weight | Block 45 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
| 554 | blk.45.ffn_up_exps.weight | Block 45 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q3_K |
- Total elements in blk.45: (~623M) 623120640
- Percentage of total elements: 2.13%