# DeepSeek-R1-Distill-Llama-8B-IQ4_NL.gguf - GGUF Internal File Dump - Endian: LITTLE endian ## Key Value Metadata Store There are 36 key-value pairs in this file | POS | TYPE | Count | Key | Value | | ---: | :------- | -----: | :------------------------------------- | :-------------------------------------------------------------------- | | 1 | UINT32 | 1 | GGUF.version | 3 | | 2 | UINT64 | 1 | GGUF.tensor_count | 292 | | 3 | UINT64 | 1 | GGUF.kv_count | 33 | | 4 | STRING | 1 | general.architecture | `llama` | | 5 | STRING | 1 | general.type | `model` | | 6 | STRING | 1 | general.name | `DeepSeek R1 Distill Llama 8B` | | 7 | STRING | 1 | general.basename | `DeepSeek-R1-Distill-Llama` | | 8 | STRING | 1 | general.size_label | `8B` | | 9 | STRING | 1 | general.license | `mit` | | 10 | UINT32 | 1 | llama.block_count | 32 | | 11 | UINT32 | 1 | llama.context_length | 131072 | | 12 | UINT32 | 1 | llama.embedding_length | 4096 | | 13 | UINT32 | 1 | llama.feed_forward_length | 14336 | | 14 | UINT32 | 1 | llama.attention.head_count | 32 | | 15 | UINT32 | 1 | llama.attention.head_count_kv | 8 | | 16 | FLOAT32 | 1 | llama.rope.freq_base | 500000.0 | | 17 | FLOAT32 | 1 | llama.attention.layer_norm_rms_epsilon | 1e-05 | | 18 | UINT32 | 1 | llama.vocab_size | 128256 | | 19 | UINT32 | 1 | llama.rope.dimension_count | 128 | | 20 | STRING | 1 | tokenizer.ggml.model | `gpt2` | | 21 | STRING | 1 | tokenizer.ggml.pre | `llama-bpe` | | 22 | [STRING] | 128256 | tokenizer.ggml.tokens | [ `!`, `"`, `#`, `$`, `%`, ... ] | | 23 | [INT32] | 128256 | tokenizer.ggml.token_type | [ 1, 1, 1, 1, 1, 1, 1, ... ] | | 24 | [STRING] | 280147 | tokenizer.ggml.merges | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ] | | 25 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 128000 | | 26 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 128001 | | 27 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 128001 | | 28 | BOOL | 1 | tokenizer.ggml.add_bos_token | True | | 29 | BOOL | 1 | tokenizer.ggml.add_eos_token | False | | 30 | STRING | 1 | tokenizer.chat_template | `{% if not add_generation_promp`...`{{'<｜Assistant｜>'}}{% endif %}` | | 31 | UINT32 | 1 | general.quantization_version | 2 | | 32 | UINT32 | 1 | general.file_type | 25 | | 33 | STRING | 1 | quantize.imatrix.file | `./imatrix/imatrix-DeepSeek-R1-Distill-Llama-8B-small.dat` | | 34 | STRING | 1 | quantize.imatrix.dataset | `../../datasets/imatrix/calibration_all_small.txt` | | 35 | INT32 | 1 | quantize.imatrix.entries_count | 225 | | 36 | INT32 | 1 | quantize.imatrix.chunks_count | 1130 | ## Tensors Overview ~8B Elements Total number of elements in all tensors: 8030261312 Elements - [DeepSeek-R1-Distill-Llama-8B-IQ4\_NL.gguf - GGUF Internal File Dump](#deepseek-r1-distill-llama-8b-iq4_nlgguf---gguf-internal-file-dump) - [Key Value Metadata Store](#key-value-metadata-store) - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements) - [Tensor Data Offset](#tensor-data-offset) - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements) - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements) - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements) - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements) - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements) - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements) - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements) - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements) - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements) - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements) - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements) - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements) - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements) - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements) - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements) - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements) - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements) - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements) - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements) - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements) - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements) - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements) - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements) - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements) - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements) - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements) - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements) - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements) - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements) - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements) - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements) - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements) - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements) ### Tensor Data Offset This table contains the offset and data segment relative to start of file | T_ID | Tensor Layer Name | Data Offset (B) | Data Size (B) | | ---: | :------------------------ | --------------: | ------------: | | 0 | output.weight | 0x779a80 | 0x119d0000 | | 1 | output_norm.weight | 0x12149a80 | 0x4000 | | 2 | rope_freqs.weight | 0x1214da80 | 0x100 | | 3 | token_embd.weight | 0x1214db80 | 0xd746000 | | 4 | blk.0.attn_k.weight | 0x1f893b80 | 0x240000 | | 5 | blk.0.attn_norm.weight | 0x1fad3b80 | 0x4000 | | 6 | blk.0.attn_output.weight | 0x1fad7b80 | 0x900000 | | 7 | blk.0.attn_q.weight | 0x203d7b80 | 0x900000 | | 8 | blk.0.attn_v.weight | 0x20cd7b80 | 0x240000 | | 9 | blk.0.ffn_down.weight | 0x20f17b80 | 0x2680000 | | 10 | blk.0.ffn_gate.weight | 0x23597b80 | 0x1f80000 | | 11 | blk.0.ffn_norm.weight | 0x25517b80 | 0x4000 | | 12 | blk.0.ffn_up.weight | 0x2551bb80 | 0x1f80000 | | 13 | blk.1.attn_k.weight | 0x2749bb80 | 0x240000 | | 14 | blk.1.attn_norm.weight | 0x276dbb80 | 0x4000 | | 15 | blk.1.attn_output.weight | 0x276dfb80 | 0x900000 | | 16 | blk.1.attn_q.weight | 0x27fdfb80 | 0x900000 | | 17 | blk.1.attn_v.weight | 0x288dfb80 | 0x240000 | | 18 | blk.1.ffn_down.weight | 0x28b1fb80 | 0x2680000 | | 19 | blk.1.ffn_gate.weight | 0x2b19fb80 | 0x1f80000 | | 20 | blk.1.ffn_norm.weight | 0x2d11fb80 | 0x4000 | | 21 | blk.1.ffn_up.weight | 0x2d123b80 | 0x1f80000 | | 22 | blk.2.attn_k.weight | 0x2f0a3b80 | 0x240000 | | 23 | blk.2.attn_norm.weight | 0x2f2e3b80 | 0x4000 | | 24 | blk.2.attn_output.weight | 0x2f2e7b80 | 0x900000 | | 25 | blk.2.attn_q.weight | 0x2fbe7b80 | 0x900000 | | 26 | blk.2.attn_v.weight | 0x304e7b80 | 0x240000 | | 27 | blk.2.ffn_down.weight | 0x30727b80 | 0x2680000 | | 28 | blk.2.ffn_gate.weight | 0x32da7b80 | 0x1f80000 | | 29 | blk.2.ffn_norm.weight | 0x34d27b80 | 0x4000 | | 30 | blk.2.ffn_up.weight | 0x34d2bb80 | 0x1f80000 | | 31 | blk.3.attn_k.weight | 0x36cabb80 | 0x240000 | | 32 | blk.3.attn_norm.weight | 0x36eebb80 | 0x4000 | | 33 | blk.3.attn_output.weight | 0x36eefb80 | 0x900000 | | 34 | blk.3.attn_q.weight | 0x377efb80 | 0x900000 | | 35 | blk.3.attn_v.weight | 0x380efb80 | 0x240000 | | 36 | blk.3.ffn_down.weight | 0x3832fb80 | 0x2680000 | | 37 | blk.3.ffn_gate.weight | 0x3a9afb80 | 0x1f80000 | | 38 | blk.3.ffn_norm.weight | 0x3c92fb80 | 0x4000 | | 39 | blk.3.ffn_up.weight | 0x3c933b80 | 0x1f80000 | | 40 | blk.4.attn_k.weight | 0x3e8b3b80 | 0x240000 | | 41 | blk.4.attn_norm.weight | 0x3eaf3b80 | 0x4000 | | 42 | blk.4.attn_output.weight | 0x3eaf7b80 | 0x900000 | | 43 | blk.4.attn_q.weight | 0x3f3f7b80 | 0x900000 | | 44 | blk.4.attn_v.weight | 0x3fcf7b80 | 0x240000 | | 45 | blk.4.ffn_down.weight | 0x3ff37b80 | 0x2680000 | | 46 | blk.4.ffn_gate.weight | 0x425b7b80 | 0x1f80000 | | 47 | blk.4.ffn_norm.weight | 0x44537b80 | 0x4000 | | 48 | blk.4.ffn_up.weight | 0x4453bb80 | 0x1f80000 | | 49 | blk.5.attn_k.weight | 0x464bbb80 | 0x240000 | | 50 | blk.5.attn_norm.weight | 0x466fbb80 | 0x4000 | | 51 | blk.5.attn_output.weight | 0x466ffb80 | 0x900000 | | 52 | blk.5.attn_q.weight | 0x46fffb80 | 0x900000 | | 53 | blk.5.attn_v.weight | 0x478ffb80 | 0x240000 | | 54 | blk.5.ffn_down.weight | 0x47b3fb80 | 0x2680000 | | 55 | blk.5.ffn_gate.weight | 0x4a1bfb80 | 0x1f80000 | | 56 | blk.5.ffn_norm.weight | 0x4c13fb80 | 0x4000 | | 57 | blk.5.ffn_up.weight | 0x4c143b80 | 0x1f80000 | | 58 | blk.6.attn_k.weight | 0x4e0c3b80 | 0x240000 | | 59 | blk.6.attn_norm.weight | 0x4e303b80 | 0x4000 | | 60 | blk.6.attn_output.weight | 0x4e307b80 | 0x900000 | | 61 | blk.6.attn_q.weight | 0x4ec07b80 | 0x900000 | | 62 | blk.6.attn_v.weight | 0x4f507b80 | 0x240000 | | 63 | blk.6.ffn_down.weight | 0x4f747b80 | 0x2680000 | | 64 | blk.6.ffn_gate.weight | 0x51dc7b80 | 0x1f80000 | | 65 | blk.6.ffn_norm.weight | 0x53d47b80 | 0x4000 | | 66 | blk.6.ffn_up.weight | 0x53d4bb80 | 0x1f80000 | | 67 | blk.7.attn_k.weight | 0x55ccbb80 | 0x240000 | | 68 | blk.7.attn_norm.weight | 0x55f0bb80 | 0x4000 | | 69 | blk.7.attn_output.weight | 0x55f0fb80 | 0x900000 | | 70 | blk.7.attn_q.weight | 0x5680fb80 | 0x900000 | | 71 | blk.7.attn_v.weight | 0x5710fb80 | 0x240000 | | 72 | blk.7.ffn_down.weight | 0x5734fb80 | 0x2680000 | | 73 | blk.7.ffn_gate.weight | 0x599cfb80 | 0x1f80000 | | 74 | blk.7.ffn_norm.weight | 0x5b94fb80 | 0x4000 | | 75 | blk.7.ffn_up.weight | 0x5b953b80 | 0x1f80000 | | 76 | blk.8.attn_k.weight | 0x5d8d3b80 | 0x240000 | | 77 | blk.8.attn_norm.weight | 0x5db13b80 | 0x4000 | | 78 | blk.8.attn_output.weight | 0x5db17b80 | 0x900000 | | 79 | blk.8.attn_q.weight | 0x5e417b80 | 0x900000 | | 80 | blk.8.attn_v.weight | 0x5ed17b80 | 0x240000 | | 81 | blk.8.ffn_down.weight | 0x5ef57b80 | 0x2680000 | | 82 | blk.8.ffn_gate.weight | 0x615d7b80 | 0x1f80000 | | 83 | blk.8.ffn_norm.weight | 0x63557b80 | 0x4000 | | 84 | blk.8.ffn_up.weight | 0x6355bb80 | 0x1f80000 | | 85 | blk.9.attn_k.weight | 0x654dbb80 | 0x240000 | | 86 | blk.9.attn_norm.weight | 0x6571bb80 | 0x4000 | | 87 | blk.9.attn_output.weight | 0x6571fb80 | 0x900000 | | 88 | blk.9.attn_q.weight | 0x6601fb80 | 0x900000 | | 89 | blk.9.attn_v.weight | 0x6691fb80 | 0x240000 | | 90 | blk.9.ffn_down.weight | 0x66b5fb80 | 0x2680000 | | 91 | blk.9.ffn_gate.weight | 0x691dfb80 | 0x1f80000 | | 92 | blk.9.ffn_norm.weight | 0x6b15fb80 | 0x4000 | | 93 | blk.9.ffn_up.weight | 0x6b163b80 | 0x1f80000 | | 94 | blk.10.attn_k.weight | 0x6d0e3b80 | 0x240000 | | 95 | blk.10.attn_norm.weight | 0x6d323b80 | 0x4000 | | 96 | blk.10.attn_output.weight | 0x6d327b80 | 0x900000 | | 97 | blk.10.attn_q.weight | 0x6dc27b80 | 0x900000 | | 98 | blk.10.attn_v.weight | 0x6e527b80 | 0x240000 | | 99 | blk.10.ffn_down.weight | 0x6e767b80 | 0x2680000 | | 100 | blk.10.ffn_gate.weight | 0x70de7b80 | 0x1f80000 | | 101 | blk.10.ffn_norm.weight | 0x72d67b80 | 0x4000 | | 102 | blk.10.ffn_up.weight | 0x72d6bb80 | 0x1f80000 | | 103 | blk.11.attn_k.weight | 0x74cebb80 | 0x240000 | | 104 | blk.11.attn_norm.weight | 0x74f2bb80 | 0x4000 | | 105 | blk.11.attn_output.weight | 0x74f2fb80 | 0x900000 | | 106 | blk.11.attn_q.weight | 0x7582fb80 | 0x900000 | | 107 | blk.11.attn_v.weight | 0x7612fb80 | 0x240000 | | 108 | blk.11.ffn_down.weight | 0x7636fb80 | 0x2680000 | | 109 | blk.11.ffn_gate.weight | 0x789efb80 | 0x1f80000 | | 110 | blk.11.ffn_norm.weight | 0x7a96fb80 | 0x4000 | | 111 | blk.11.ffn_up.weight | 0x7a973b80 | 0x1f80000 | | 112 | blk.12.attn_k.weight | 0x7c8f3b80 | 0x240000 | | 113 | blk.12.attn_norm.weight | 0x7cb33b80 | 0x4000 | | 114 | blk.12.attn_output.weight | 0x7cb37b80 | 0x900000 | | 115 | blk.12.attn_q.weight | 0x7d437b80 | 0x900000 | | 116 | blk.12.attn_v.weight | 0x7dd37b80 | 0x240000 | | 117 | blk.12.ffn_down.weight | 0x7df77b80 | 0x2680000 | | 118 | blk.12.ffn_gate.weight | 0x805f7b80 | 0x1f80000 | | 119 | blk.12.ffn_norm.weight | 0x82577b80 | 0x4000 | | 120 | blk.12.ffn_up.weight | 0x8257bb80 | 0x1f80000 | | 121 | blk.13.attn_k.weight | 0x844fbb80 | 0x240000 | | 122 | blk.13.attn_norm.weight | 0x8473bb80 | 0x4000 | | 123 | blk.13.attn_output.weight | 0x8473fb80 | 0x900000 | | 124 | blk.13.attn_q.weight | 0x8503fb80 | 0x900000 | | 125 | blk.13.attn_v.weight | 0x8593fb80 | 0x240000 | | 126 | blk.13.ffn_down.weight | 0x85b7fb80 | 0x2680000 | | 127 | blk.13.ffn_gate.weight | 0x881ffb80 | 0x1f80000 | | 128 | blk.13.ffn_norm.weight | 0x8a17fb80 | 0x4000 | | 129 | blk.13.ffn_up.weight | 0x8a183b80 | 0x1f80000 | | 130 | blk.14.attn_k.weight | 0x8c103b80 | 0x240000 | | 131 | blk.14.attn_norm.weight | 0x8c343b80 | 0x4000 | | 132 | blk.14.attn_output.weight | 0x8c347b80 | 0x900000 | | 133 | blk.14.attn_q.weight | 0x8cc47b80 | 0x900000 | | 134 | blk.14.attn_v.weight | 0x8d547b80 | 0x240000 | | 135 | blk.14.ffn_down.weight | 0x8d787b80 | 0x2680000 | | 136 | blk.14.ffn_gate.weight | 0x8fe07b80 | 0x1f80000 | | 137 | blk.14.ffn_norm.weight | 0x91d87b80 | 0x4000 | | 138 | blk.14.ffn_up.weight | 0x91d8bb80 | 0x1f80000 | | 139 | blk.15.attn_k.weight | 0x93d0bb80 | 0x240000 | | 140 | blk.15.attn_norm.weight | 0x93f4bb80 | 0x4000 | | 141 | blk.15.attn_output.weight | 0x93f4fb80 | 0x900000 | | 142 | blk.15.attn_q.weight | 0x9484fb80 | 0x900000 | | 143 | blk.15.attn_v.weight | 0x9514fb80 | 0x240000 | | 144 | blk.15.ffn_down.weight | 0x9538fb80 | 0x2680000 | | 145 | blk.15.ffn_gate.weight | 0x97a0fb80 | 0x1f80000 | | 146 | blk.15.ffn_norm.weight | 0x9998fb80 | 0x4000 | | 147 | blk.15.ffn_up.weight | 0x99993b80 | 0x1f80000 | | 148 | blk.16.attn_k.weight | 0x9b913b80 | 0x1b8000 | | 149 | blk.16.attn_norm.weight | 0x9bacbb80 | 0x4000 | | 150 | blk.16.attn_output.weight | 0x9bacfb80 | 0x900000 | | 151 | blk.16.attn_q.weight | 0x9c3cfb80 | 0x6e0000 | | 152 | blk.16.attn_v.weight | 0x9caafb80 | 0x220000 | | 153 | blk.16.ffn_down.weight | 0x9cccfb80 | 0x2680000 | | 154 | blk.16.ffn_gate.weight | 0x9f34fb80 | 0x1810000 | | 155 | blk.16.ffn_norm.weight | 0xa0b5fb80 | 0x4000 | | 156 | blk.16.ffn_up.weight | 0xa0b63b80 | 0x1810000 | | 157 | blk.17.attn_k.weight | 0xa2373b80 | 0x1b8000 | | 158 | blk.17.attn_norm.weight | 0xa252bb80 | 0x4000 | | 159 | blk.17.attn_output.weight | 0xa252fb80 | 0x900000 | | 160 | blk.17.attn_q.weight | 0xa2e2fb80 | 0x6e0000 | | 161 | blk.17.attn_v.weight | 0xa350fb80 | 0x220000 | | 162 | blk.17.ffn_down.weight | 0xa372fb80 | 0x2680000 | | 163 | blk.17.ffn_gate.weight | 0xa5dafb80 | 0x1810000 | | 164 | blk.17.ffn_norm.weight | 0xa75bfb80 | 0x4000 | | 165 | blk.17.ffn_up.weight | 0xa75c3b80 | 0x1810000 | | 166 | blk.18.attn_k.weight | 0xa8dd3b80 | 0x1b8000 | | 167 | blk.18.attn_norm.weight | 0xa8f8bb80 | 0x4000 | | 168 | blk.18.attn_output.weight | 0xa8f8fb80 | 0x900000 | | 169 | blk.18.attn_q.weight | 0xa988fb80 | 0x6e0000 | | 170 | blk.18.attn_v.weight | 0xa9f6fb80 | 0x220000 | | 171 | blk.18.ffn_down.weight | 0xaa18fb80 | 0x2680000 | | 172 | blk.18.ffn_gate.weight | 0xac80fb80 | 0x1810000 | | 173 | blk.18.ffn_norm.weight | 0xae01fb80 | 0x4000 | | 174 | blk.18.ffn_up.weight | 0xae023b80 | 0x1810000 | | 175 | blk.19.attn_k.weight | 0xaf833b80 | 0x1b8000 | | 176 | blk.19.attn_norm.weight | 0xaf9ebb80 | 0x4000 | | 177 | blk.19.attn_output.weight | 0xaf9efb80 | 0x900000 | | 178 | blk.19.attn_q.weight | 0xb02efb80 | 0x6e0000 | | 179 | blk.19.attn_v.weight | 0xb09cfb80 | 0x220000 | | 180 | blk.19.ffn_down.weight | 0xb0befb80 | 0x2680000 | | 181 | blk.19.ffn_gate.weight | 0xb326fb80 | 0x1810000 | | 182 | blk.19.ffn_norm.weight | 0xb4a7fb80 | 0x4000 | | 183 | blk.19.ffn_up.weight | 0xb4a83b80 | 0x1810000 | | 184 | blk.20.attn_k.weight | 0xb6293b80 | 0x1b8000 | | 185 | blk.20.attn_norm.weight | 0xb644bb80 | 0x4000 | | 186 | blk.20.attn_output.weight | 0xb644fb80 | 0x900000 | | 187 | blk.20.attn_q.weight | 0xb6d4fb80 | 0x6e0000 | | 188 | blk.20.attn_v.weight | 0xb742fb80 | 0x220000 | | 189 | blk.20.ffn_down.weight | 0xb764fb80 | 0x2680000 | | 190 | blk.20.ffn_gate.weight | 0xb9ccfb80 | 0x1810000 | | 191 | blk.20.ffn_norm.weight | 0xbb4dfb80 | 0x4000 | | 192 | blk.20.ffn_up.weight | 0xbb4e3b80 | 0x1810000 | | 193 | blk.21.attn_k.weight | 0xbccf3b80 | 0x1b8000 | | 194 | blk.21.attn_norm.weight | 0xbceabb80 | 0x4000 | | 195 | blk.21.attn_output.weight | 0xbceafb80 | 0x900000 | | 196 | blk.21.attn_q.weight | 0xbd7afb80 | 0x6e0000 | | 197 | blk.21.attn_v.weight | 0xbde8fb80 | 0x220000 | | 198 | blk.21.ffn_down.weight | 0xbe0afb80 | 0x2680000 | | 199 | blk.21.ffn_gate.weight | 0xc072fb80 | 0x1810000 | | 200 | blk.21.ffn_norm.weight | 0xc1f3fb80 | 0x4000 | | 201 | blk.21.ffn_up.weight | 0xc1f43b80 | 0x1810000 | | 202 | blk.22.attn_k.weight | 0xc3753b80 | 0x1b8000 | | 203 | blk.22.attn_norm.weight | 0xc390bb80 | 0x4000 | | 204 | blk.22.attn_output.weight | 0xc390fb80 | 0x900000 | | 205 | blk.22.attn_q.weight | 0xc420fb80 | 0x6e0000 | | 206 | blk.22.attn_v.weight | 0xc48efb80 | 0x220000 | | 207 | blk.22.ffn_down.weight | 0xc4b0fb80 | 0x2680000 | | 208 | blk.22.ffn_gate.weight | 0xc718fb80 | 0x1810000 | | 209 | blk.22.ffn_norm.weight | 0xc899fb80 | 0x4000 | | 210 | blk.22.ffn_up.weight | 0xc89a3b80 | 0x1810000 | | 211 | blk.23.attn_k.weight | 0xca1b3b80 | 0x1b8000 | | 212 | blk.23.attn_norm.weight | 0xca36bb80 | 0x4000 | | 213 | blk.23.attn_output.weight | 0xca36fb80 | 0x900000 | | 214 | blk.23.attn_q.weight | 0xcac6fb80 | 0x6e0000 | | 215 | blk.23.attn_v.weight | 0xcb34fb80 | 0x220000 | | 216 | blk.23.ffn_down.weight | 0xcb56fb80 | 0x2680000 | | 217 | blk.23.ffn_gate.weight | 0xcdbefb80 | 0x1810000 | | 218 | blk.23.ffn_norm.weight | 0xcf3ffb80 | 0x4000 | | 219 | blk.23.ffn_up.weight | 0xcf403b80 | 0x1810000 | | 220 | blk.24.attn_k.weight | 0xd0c13b80 | 0x1b8000 | | 221 | blk.24.attn_norm.weight | 0xd0dcbb80 | 0x4000 | | 222 | blk.24.attn_output.weight | 0xd0dcfb80 | 0x900000 | | 223 | blk.24.attn_q.weight | 0xd16cfb80 | 0x6e0000 | | 224 | blk.24.attn_v.weight | 0xd1dafb80 | 0x220000 | | 225 | blk.24.ffn_down.weight | 0xd1fcfb80 | 0x2680000 | | 226 | blk.24.ffn_gate.weight | 0xd464fb80 | 0x1810000 | | 227 | blk.24.ffn_norm.weight | 0xd5e5fb80 | 0x4000 | | 228 | blk.24.ffn_up.weight | 0xd5e63b80 | 0x1810000 | | 229 | blk.25.attn_k.weight | 0xd7673b80 | 0x1b8000 | | 230 | blk.25.attn_norm.weight | 0xd782bb80 | 0x4000 | | 231 | blk.25.attn_output.weight | 0xd782fb80 | 0x900000 | | 232 | blk.25.attn_q.weight | 0xd812fb80 | 0x6e0000 | | 233 | blk.25.attn_v.weight | 0xd880fb80 | 0x220000 | | 234 | blk.25.ffn_down.weight | 0xd8a2fb80 | 0x2680000 | | 235 | blk.25.ffn_gate.weight | 0xdb0afb80 | 0x1810000 | | 236 | blk.25.ffn_norm.weight | 0xdc8bfb80 | 0x4000 | | 237 | blk.25.ffn_up.weight | 0xdc8c3b80 | 0x1810000 | | 238 | blk.26.attn_k.weight | 0xde0d3b80 | 0x1b8000 | | 239 | blk.26.attn_norm.weight | 0xde28bb80 | 0x4000 | | 240 | blk.26.attn_output.weight | 0xde28fb80 | 0x900000 | | 241 | blk.26.attn_q.weight | 0xdeb8fb80 | 0x6e0000 | | 242 | blk.26.attn_v.weight | 0xdf26fb80 | 0x220000 | | 243 | blk.26.ffn_down.weight | 0xdf48fb80 | 0x2680000 | | 244 | blk.26.ffn_gate.weight | 0xe1b0fb80 | 0x1810000 | | 245 | blk.26.ffn_norm.weight | 0xe331fb80 | 0x4000 | | 246 | blk.26.ffn_up.weight | 0xe3323b80 | 0x1810000 | | 247 | blk.27.attn_k.weight | 0xe4b33b80 | 0x1b8000 | | 248 | blk.27.attn_norm.weight | 0xe4cebb80 | 0x4000 | | 249 | blk.27.attn_output.weight | 0xe4cefb80 | 0x900000 | | 250 | blk.27.attn_q.weight | 0xe55efb80 | 0x6e0000 | | 251 | blk.27.attn_v.weight | 0xe5ccfb80 | 0x220000 | | 252 | blk.27.ffn_down.weight | 0xe5eefb80 | 0x2680000 | | 253 | blk.27.ffn_gate.weight | 0xe856fb80 | 0x1810000 | | 254 | blk.27.ffn_norm.weight | 0xe9d7fb80 | 0x4000 | | 255 | blk.27.ffn_up.weight | 0xe9d83b80 | 0x1810000 | | 256 | blk.28.attn_k.weight | 0xeb593b80 | 0x1b8000 | | 257 | blk.28.attn_norm.weight | 0xeb74bb80 | 0x4000 | | 258 | blk.28.attn_output.weight | 0xeb74fb80 | 0x900000 | | 259 | blk.28.attn_q.weight | 0xec04fb80 | 0x6e0000 | | 260 | blk.28.attn_v.weight | 0xec72fb80 | 0x220000 | | 261 | blk.28.ffn_down.weight | 0xec94fb80 | 0x2680000 | | 262 | blk.28.ffn_gate.weight | 0xeefcfb80 | 0x1810000 | | 263 | blk.28.ffn_norm.weight | 0xf07dfb80 | 0x4000 | | 264 | blk.28.ffn_up.weight | 0xf07e3b80 | 0x1810000 | | 265 | blk.29.attn_k.weight | 0xf1ff3b80 | 0x1b8000 | | 266 | blk.29.attn_norm.weight | 0xf21abb80 | 0x4000 | | 267 | blk.29.attn_output.weight | 0xf21afb80 | 0x900000 | | 268 | blk.29.attn_q.weight | 0xf2aafb80 | 0x6e0000 | | 269 | blk.29.attn_v.weight | 0xf318fb80 | 0x220000 | | 270 | blk.29.ffn_down.weight | 0xf33afb80 | 0x2680000 | | 271 | blk.29.ffn_gate.weight | 0xf5a2fb80 | 0x1810000 | | 272 | blk.29.ffn_norm.weight | 0xf723fb80 | 0x4000 | | 273 | blk.29.ffn_up.weight | 0xf7243b80 | 0x1810000 | | 274 | blk.30.attn_k.weight | 0xf8a53b80 | 0x1b8000 | | 275 | blk.30.attn_norm.weight | 0xf8c0bb80 | 0x4000 | | 276 | blk.30.attn_output.weight | 0xf8c0fb80 | 0x900000 | | 277 | blk.30.attn_q.weight | 0xf950fb80 | 0x6e0000 | | 278 | blk.30.attn_v.weight | 0xf9befb80 | 0x220000 | | 279 | blk.30.ffn_down.weight | 0xf9e0fb80 | 0x2680000 | | 280 | blk.30.ffn_gate.weight | 0xfc48fb80 | 0x1810000 | | 281 | blk.30.ffn_norm.weight | 0xfdc9fb80 | 0x4000 | | 282 | blk.30.ffn_up.weight | 0xfdca3b80 | 0x1810000 | | 283 | blk.31.attn_k.weight | 0xff4b3b80 | 0x1b8000 | | 284 | blk.31.attn_norm.weight | 0xff66bb80 | 0x4000 | | 285 | blk.31.attn_output.weight | 0xff66fb80 | 0x900000 | | 286 | blk.31.attn_q.weight | 0xfff6fb80 | 0x6e0000 | | 287 | blk.31.attn_v.weight | 0x10064fb80 | 0x220000 | | 288 | blk.31.ffn_down.weight | 0x10086fb80 | 0x2680000 | | 289 | blk.31.ffn_gate.weight | 0x102eefb80 | 0x1810000 | | 290 | blk.31.ffn_norm.weight | 0x1046ffb80 | 0x4000 | | 291 | blk.31.ffn_up.weight | 0x104703b80 | 0x1810000 | ### Base Tensor Group : ~1B Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------- | :------------------------------- | :---------------- | :-------------------- | :----- | | 0 | output.weight | Output (W) | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ4_NL | | 1 | output_norm.weight | Output Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 2 | rope_freqs.weight | Rope_Freqs (W) | ( 64) 64 | 64 x 1 x 1 x 1 | F32 | | 3 | token_embd.weight | Token Embedding (W) | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ3_S | - Total elements in base: ( ~1B) 1050677312 - Percentage of total elements: 13.08% ### Block 0 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------------- | :--------------------------------------------- | :-------------- | :-------------------- | :----- | | 4 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 5 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 6 | blk.0.attn_output.weight | Block 0 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 7 | blk.0.attn_q.weight | Block 0 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 8 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 9 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 10 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 11 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 12 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.0: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 1 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------------- | :--------------------------------------------- | :-------------- | :-------------------- | :----- | | 13 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 14 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 15 | blk.1.attn_output.weight | Block 1 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 16 | blk.1.attn_q.weight | Block 1 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 17 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 18 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 19 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 20 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 21 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.1: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 2 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------------- | :--------------------------------------------- | :-------------- | :-------------------- | :----- | | 22 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 23 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 24 | blk.2.attn_output.weight | Block 2 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 25 | blk.2.attn_q.weight | Block 2 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 26 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 27 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 28 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 29 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 30 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.2: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 3 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------------- | :--------------------------------------------- | :-------------- | :-------------------- | :----- | | 31 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 32 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 33 | blk.3.attn_output.weight | Block 3 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 34 | blk.3.attn_q.weight | Block 3 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 35 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 36 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 37 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 38 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 39 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.3: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 4 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------------- | :--------------------------------------------- | :-------------- | :-------------------- | :----- | | 40 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 41 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 42 | blk.4.attn_output.weight | Block 4 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 43 | blk.4.attn_q.weight | Block 4 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 44 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 45 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 46 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 47 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 48 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.4: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 5 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------------- | :--------------------------------------------- | :-------------- | :-------------------- | :----- | | 49 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 50 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 51 | blk.5.attn_output.weight | Block 5 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 52 | blk.5.attn_q.weight | Block 5 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 53 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 54 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 55 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 56 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 57 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.5: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 6 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------------- | :--------------------------------------------- | :-------------- | :-------------------- | :----- | | 58 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 59 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 60 | blk.6.attn_output.weight | Block 6 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 61 | blk.6.attn_q.weight | Block 6 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 62 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 63 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 64 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 65 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 66 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.6: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 7 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------------- | :--------------------------------------------- | :-------------- | :-------------------- | :----- | | 67 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 68 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 69 | blk.7.attn_output.weight | Block 7 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 70 | blk.7.attn_q.weight | Block 7 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 71 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 72 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 73 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 74 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 75 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.7: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 8 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------------- | :--------------------------------------------- | :-------------- | :-------------------- | :----- | | 76 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 77 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 78 | blk.8.attn_output.weight | Block 8 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 79 | blk.8.attn_q.weight | Block 8 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 80 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 81 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 82 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 83 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 84 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.8: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 9 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :----------------------- | :--------------------------------------------- | :-------------- | :-------------------- | :----- | | 85 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 86 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 87 | blk.9.attn_output.weight | Block 9 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 88 | blk.9.attn_q.weight | Block 9 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 89 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 90 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 91 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 92 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 93 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.9: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 10 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 94 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 95 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 96 | blk.10.attn_output.weight | Block 10 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 97 | blk.10.attn_q.weight | Block 10 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 98 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 99 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 100 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 101 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 102 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.10: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 11 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 103 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 104 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 105 | blk.11.attn_output.weight | Block 11 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 106 | blk.11.attn_q.weight | Block 11 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 107 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 108 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 109 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 110 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 111 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.11: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 12 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 112 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 113 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 114 | blk.12.attn_output.weight | Block 12 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 115 | blk.12.attn_q.weight | Block 12 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 116 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 117 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 118 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 119 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 120 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.12: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 13 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 121 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 122 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 123 | blk.13.attn_output.weight | Block 13 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 124 | blk.13.attn_q.weight | Block 13 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 125 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 126 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 127 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 128 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 129 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.13: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 14 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 130 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 131 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 132 | blk.14.attn_output.weight | Block 14 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 133 | blk.14.attn_q.weight | Block 14 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 134 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 135 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 136 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 137 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 138 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.14: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 15 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 139 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 140 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 141 | blk.15.attn_output.weight | Block 15 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 142 | blk.15.attn_q.weight | Block 15 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 143 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_NL | | 144 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 145 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | | 146 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 147 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ4_NL | - Total elements in blk.15: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 16 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 148 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 149 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 150 | blk.16.attn_output.weight | Block 16 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 151 | blk.16.attn_q.weight | Block 16 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 152 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 153 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 154 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 155 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 156 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.16: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 17 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 157 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 158 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 159 | blk.17.attn_output.weight | Block 17 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 160 | blk.17.attn_q.weight | Block 17 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 161 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 162 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 163 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 164 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 165 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.17: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 18 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 166 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 167 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 168 | blk.18.attn_output.weight | Block 18 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 169 | blk.18.attn_q.weight | Block 18 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 170 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 171 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 172 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 173 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 174 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.18: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 19 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 175 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 176 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 177 | blk.19.attn_output.weight | Block 19 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 178 | blk.19.attn_q.weight | Block 19 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 179 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 180 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 181 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 182 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 183 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.19: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 20 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 184 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 185 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 186 | blk.20.attn_output.weight | Block 20 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 187 | blk.20.attn_q.weight | Block 20 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 188 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 189 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 190 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 191 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 192 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.20: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 21 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 193 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 194 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 195 | blk.21.attn_output.weight | Block 21 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 196 | blk.21.attn_q.weight | Block 21 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 197 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 198 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 199 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 200 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 201 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.21: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 22 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 202 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 203 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 204 | blk.22.attn_output.weight | Block 22 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 205 | blk.22.attn_q.weight | Block 22 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 206 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 207 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 208 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 209 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 210 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.22: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 23 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 211 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 212 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 213 | blk.23.attn_output.weight | Block 23 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 214 | blk.23.attn_q.weight | Block 23 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 215 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 216 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 217 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 218 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 219 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.23: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 24 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 220 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 221 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 222 | blk.24.attn_output.weight | Block 24 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 223 | blk.24.attn_q.weight | Block 24 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 224 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 225 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 226 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 227 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 228 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.24: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 25 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 229 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 230 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 231 | blk.25.attn_output.weight | Block 25 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 232 | blk.25.attn_q.weight | Block 25 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 233 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 234 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 235 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 236 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 237 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.25: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 26 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 238 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 239 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 240 | blk.26.attn_output.weight | Block 26 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 241 | blk.26.attn_q.weight | Block 26 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 242 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 243 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 244 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 245 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 246 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.26: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 27 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 247 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 248 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 249 | blk.27.attn_output.weight | Block 27 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 250 | blk.27.attn_q.weight | Block 27 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 251 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 252 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 253 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 254 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 255 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.27: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 28 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 256 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 257 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 258 | blk.28.attn_output.weight | Block 28 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 259 | blk.28.attn_q.weight | Block 28 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 260 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 261 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 262 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 263 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 264 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.28: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 29 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 265 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 266 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 267 | blk.29.attn_output.weight | Block 29 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 268 | blk.29.attn_q.weight | Block 29 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 269 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 270 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 271 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 272 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 273 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.29: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 30 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 274 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 275 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 276 | blk.30.attn_output.weight | Block 30 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 277 | blk.30.attn_q.weight | Block 30 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 278 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 279 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 280 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 281 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 282 | blk.30.ffn_up.weight | Block 30 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.30: (~218M) 218112000 - Percentage of total elements: 2.72% ### Block 31 Tensor Group : ~218M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | ---: | :------------------------ | :---------------------------------------------- | :-------------- | :-------------------- | :----- | | 283 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ3_S | | 284 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 285 | blk.31.attn_output.weight | Block 31 Attention Output (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ4_NL | | 286 | blk.31.attn_q.weight | Block 31 Attention Query (W) | (~17M) 16777216 | 4096 x 4096 x 1 x 1 | IQ3_S | | 287 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~4M) 4194304 | 4096 x 1024 x 1 x 1 | IQ4_XS | | 288 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~59M) 58720256 | 14336 x 4096 x 1 x 1 | Q5_K | | 289 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | | 290 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~4K) 4096 | 4096 x 1 x 1 x 1 | F32 | | 291 | blk.31.ffn_up.weight | Block 31 Feed-Forward Network "Up" (W) | (~59M) 58720256 | 4096 x 14336 x 1 x 1 | IQ3_S | - Total elements in blk.31: (~218M) 218112000 - Percentage of total elements: 2.72%