| # Dolphin-Mistral-24B-Venice-Edition-IQ4_NL.gguf - GGUF Internal File Dump | |
| - Endian: LITTLE endian | |
| ## Key Value Metadata Store | |
| There are 46 key-value pairs in this file | |
| | POS | TYPE | Count | Key | Value | | |
| |----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------| | |
| | 1 | UINT32 | 1 | GGUF.version | 3 | | |
| | 2 | UINT64 | 1 | GGUF.tensor_count | 363 | | |
| | 3 | UINT64 | 1 | GGUF.kv_count | 43 | | |
| | 4 | STRING | 1 | general.architecture | `llama` | | |
| | 5 | STRING | 1 | general.type | `model` | | |
| | 6 | STRING | 1 | general.name | `Dolphin Mistral 24B Venice Edition` | | |
| | 7 | STRING | 1 | general.finetune | `Venice-Edition` | | |
| | 8 | STRING | 1 | general.basename | `Dolphin-Mistral` | | |
| | 9 | STRING | 1 | general.size_label | `24B` | | |
| | 10 | STRING | 1 | general.license | `apache-2.0` | | |
| | 11 | UINT32 | 1 | general.base_model.count | 1 | | |
| | 12 | STRING | 1 | general.base_model.0.name | `Mistral Small 24B Instruct 2501` | | |
| | 13 | STRING | 1 | general.base_model.0.version | `2501` | | |
| | 14 | STRING | 1 | general.base_model.0.organization | `Mistralai` | | |
| | 15 | STRING | 1 | general.base_model.0.repo_url | `https://huggingface.co/mistral`...`istral-Small-24B-Instruct-2501` | | |
| | 16 | UINT32 | 1 | llama.block_count | 40 | | |
| | 17 | UINT32 | 1 | llama.context_length | 32768 | | |
| | 18 | UINT32 | 1 | llama.embedding_length | 5120 | | |
| | 19 | UINT32 | 1 | llama.feed_forward_length | 32768 | | |
| | 20 | UINT32 | 1 | llama.attention.head_count | 32 | | |
| | 21 | UINT32 | 1 | llama.attention.head_count_kv | 8 | | |
| | 22 | FLOAT32 | 1 | llama.rope.freq_base | 100000000.0 | | |
| | 23 | FLOAT32 | 1 | llama.attention.layer_norm_rms_epsilon | 1e-05 | | |
| | 24 | UINT32 | 1 | llama.attention.key_length | 128 | | |
| | 25 | UINT32 | 1 | llama.attention.value_length | 128 | | |
| | 26 | UINT32 | 1 | llama.vocab_size | 131072 | | |
| | 27 | UINT32 | 1 | llama.rope.dimension_count | 128 | | |
| | 28 | STRING | 1 | tokenizer.ggml.model | `gpt2` | | |
| | 29 | STRING | 1 | tokenizer.ggml.pre | `tekken` | | |
| | 30 | [STRING] | 131072 | tokenizer.ggml.tokens | [ `<unk>`, `<s>`, `</s>`, `[INST]`, `[/INST]`, ... ] | | |
| | 31 | [INT32] | 131072 | tokenizer.ggml.token_type | [ 3, 3, 3, 3, 3, 3, 3, ... ] | | |
| | 32 | [STRING] | 269443 | tokenizer.ggml.merges | [ `Ġ Ġ`, `Ġ t`, `e r`, `i n`, `Ġ ĠĠĠ`, ... ] | | |
| | 33 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 1 | | |
| | 34 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 2 | | |
| | 35 | UINT32 | 1 | tokenizer.ggml.unknown_token_id | 0 | | |
| | 36 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 11 | | |
| | 37 | BOOL | 1 | tokenizer.ggml.add_bos_token | True | | |
| | 38 | BOOL | 1 | tokenizer.ggml.add_eos_token | False | | |
| | 39 | STRING | 1 | tokenizer.chat_template | `{%- set today = strftime_now("`...` {%- endif %}{%- endfor %}` | | |
| | 40 | BOOL | 1 | tokenizer.ggml.add_space_prefix | False | | |
| | 41 | UINT32 | 1 | general.quantization_version | 2 | | |
| | 42 | UINT32 | 1 | general.file_type | 25 | | |
| | 43 | STRING | 1 | quantize.imatrix.file | `./imatrix/imatrix-Dolphin-Mist`...`l-24B-Venice-Edition-small.dat` | | |
| | 44 | STRING | 1 | quantize.imatrix.dataset | `../../datasets/imatrix/combined_eur_small.txt` | | |
| | 45 | INT32 | 1 | quantize.imatrix.entries_count | 281 | | |
| | 46 | INT32 | 1 | quantize.imatrix.chunks_count | 3192 | | |
| ## Tensors Overview ~24B Elements | |
| Total number of elements in all tensors: 23572403200 Elements | |
| - [Dolphin-Mistral-24B-Venice-Edition-IQ4\_NL.gguf - GGUF Internal File Dump](#dolphin-mistral-24b-venice-edition-iq4_nlgguf---gguf-internal-file-dump) | |
| - [Key Value Metadata Store](#key-value-metadata-store) | |
| - [Tensors Overview ~24B Elements](#tensors-overview-24b-elements) | |
| - [Tensor Data Offset](#tensor-data-offset) | |
| - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements) | |
| - [Block 0 Tensor Group : ~556M Elements](#block-0-tensor-group--556m-elements) | |
| - [Block 1 Tensor Group : ~556M Elements](#block-1-tensor-group--556m-elements) | |
| - [Block 2 Tensor Group : ~556M Elements](#block-2-tensor-group--556m-elements) | |
| - [Block 3 Tensor Group : ~556M Elements](#block-3-tensor-group--556m-elements) | |
| - [Block 4 Tensor Group : ~556M Elements](#block-4-tensor-group--556m-elements) | |
| - [Block 5 Tensor Group : ~556M Elements](#block-5-tensor-group--556m-elements) | |
| - [Block 6 Tensor Group : ~556M Elements](#block-6-tensor-group--556m-elements) | |
| - [Block 7 Tensor Group : ~556M Elements](#block-7-tensor-group--556m-elements) | |
| - [Block 8 Tensor Group : ~556M Elements](#block-8-tensor-group--556m-elements) | |
| - [Block 9 Tensor Group : ~556M Elements](#block-9-tensor-group--556m-elements) | |
| - [Block 10 Tensor Group : ~556M Elements](#block-10-tensor-group--556m-elements) | |
| - [Block 11 Tensor Group : ~556M Elements](#block-11-tensor-group--556m-elements) | |
| - [Block 12 Tensor Group : ~556M Elements](#block-12-tensor-group--556m-elements) | |
| - [Block 13 Tensor Group : ~556M Elements](#block-13-tensor-group--556m-elements) | |
| - [Block 14 Tensor Group : ~556M Elements](#block-14-tensor-group--556m-elements) | |
| - [Block 15 Tensor Group : ~556M Elements](#block-15-tensor-group--556m-elements) | |
| - [Block 16 Tensor Group : ~556M Elements](#block-16-tensor-group--556m-elements) | |
| - [Block 17 Tensor Group : ~556M Elements](#block-17-tensor-group--556m-elements) | |
| - [Block 18 Tensor Group : ~556M Elements](#block-18-tensor-group--556m-elements) | |
| - [Block 19 Tensor Group : ~556M Elements](#block-19-tensor-group--556m-elements) | |
| - [Block 20 Tensor Group : ~556M Elements](#block-20-tensor-group--556m-elements) | |
| - [Block 21 Tensor Group : ~556M Elements](#block-21-tensor-group--556m-elements) | |
| - [Block 22 Tensor Group : ~556M Elements](#block-22-tensor-group--556m-elements) | |
| - [Block 23 Tensor Group : ~556M Elements](#block-23-tensor-group--556m-elements) | |
| - [Block 24 Tensor Group : ~556M Elements](#block-24-tensor-group--556m-elements) | |
| - [Block 25 Tensor Group : ~556M Elements](#block-25-tensor-group--556m-elements) | |
| - [Block 26 Tensor Group : ~556M Elements](#block-26-tensor-group--556m-elements) | |
| - [Block 27 Tensor Group : ~556M Elements](#block-27-tensor-group--556m-elements) | |
| - [Block 28 Tensor Group : ~556M Elements](#block-28-tensor-group--556m-elements) | |
| - [Block 29 Tensor Group : ~556M Elements](#block-29-tensor-group--556m-elements) | |
| - [Block 30 Tensor Group : ~556M Elements](#block-30-tensor-group--556m-elements) | |
| - [Block 31 Tensor Group : ~556M Elements](#block-31-tensor-group--556m-elements) | |
| - [Block 32 Tensor Group : ~556M Elements](#block-32-tensor-group--556m-elements) | |
| - [Block 33 Tensor Group : ~556M Elements](#block-33-tensor-group--556m-elements) | |
| - [Block 34 Tensor Group : ~556M Elements](#block-34-tensor-group--556m-elements) | |
| - [Block 35 Tensor Group : ~556M Elements](#block-35-tensor-group--556m-elements) | |
| - [Block 36 Tensor Group : ~556M Elements](#block-36-tensor-group--556m-elements) | |
| - [Block 37 Tensor Group : ~556M Elements](#block-37-tensor-group--556m-elements) | |
| - [Block 38 Tensor Group : ~556M Elements](#block-38-tensor-group--556m-elements) | |
| - [Block 39 Tensor Group : ~556M Elements](#block-39-tensor-group--556m-elements) | |
| ### Tensor Data Offset | |
| This table contains the offset and data segment relative to start of file | |
| | T_ID | Tensor Layer Name | Data Offset (B) | Data Size (B) | | |
| |-----:|:--------------------------|-----------------:|-----------------:| | |
| | 0 | output.weight | 0x784920 | 0x16800000 | | |
| | 1 | output_norm.weight | 0x16f84920 | 0x5000 | | |
| | 2 | token_embd.weight | 0x16f89920 | 0x11300000 | | |
| | 3 | blk.0.attn_k.weight | 0x28289920 | 0x226000 | | |
| | 4 | blk.0.attn_norm.weight | 0x284af920 | 0x5000 | | |
| | 5 | blk.0.attn_output.weight | 0x284b4920 | 0xb40000 | | |
| | 6 | blk.0.attn_q.weight | 0x28ff4920 | 0x898000 | | |
| | 7 | blk.0.attn_v.weight | 0x2988c920 | 0x2a8000 | | |
| | 8 | blk.0.ffn_down.weight | 0x29b34920 | 0x5a00000 | | |
| | 9 | blk.0.ffn_gate.weight | 0x2f534920 | 0x44c0000 | | |
| | 10 | blk.0.ffn_norm.weight | 0x339f4920 | 0x5000 | | |
| | 11 | blk.0.ffn_up.weight | 0x339f9920 | 0x44c0000 | | |
| | 12 | blk.1.attn_k.weight | 0x37eb9920 | 0x226000 | | |
| | 13 | blk.1.attn_norm.weight | 0x380df920 | 0x5000 | | |
| | 14 | blk.1.attn_output.weight | 0x380e4920 | 0xb40000 | | |
| | 15 | blk.1.attn_q.weight | 0x38c24920 | 0x898000 | | |
| | 16 | blk.1.attn_v.weight | 0x394bc920 | 0x2a8000 | | |
| | 17 | blk.1.ffn_down.weight | 0x39764920 | 0x5a00000 | | |
| | 18 | blk.1.ffn_gate.weight | 0x3f164920 | 0x44c0000 | | |
| | 19 | blk.1.ffn_norm.weight | 0x43624920 | 0x5000 | | |
| | 20 | blk.1.ffn_up.weight | 0x43629920 | 0x44c0000 | | |
| | 21 | blk.2.attn_k.weight | 0x47ae9920 | 0x226000 | | |
| | 22 | blk.2.attn_norm.weight | 0x47d0f920 | 0x5000 | | |
| | 23 | blk.2.attn_output.weight | 0x47d14920 | 0xb40000 | | |
| | 24 | blk.2.attn_q.weight | 0x48854920 | 0x898000 | | |
| | 25 | blk.2.attn_v.weight | 0x490ec920 | 0x2a8000 | | |
| | 26 | blk.2.ffn_down.weight | 0x49394920 | 0x5a00000 | | |
| | 27 | blk.2.ffn_gate.weight | 0x4ed94920 | 0x44c0000 | | |
| | 28 | blk.2.ffn_norm.weight | 0x53254920 | 0x5000 | | |
| | 29 | blk.2.ffn_up.weight | 0x53259920 | 0x44c0000 | | |
| | 30 | blk.3.attn_k.weight | 0x57719920 | 0x226000 | | |
| | 31 | blk.3.attn_norm.weight | 0x5793f920 | 0x5000 | | |
| | 32 | blk.3.attn_output.weight | 0x57944920 | 0xb40000 | | |
| | 33 | blk.3.attn_q.weight | 0x58484920 | 0x898000 | | |
| | 34 | blk.3.attn_v.weight | 0x58d1c920 | 0x2a8000 | | |
| | 35 | blk.3.ffn_down.weight | 0x58fc4920 | 0x5a00000 | | |
| | 36 | blk.3.ffn_gate.weight | 0x5e9c4920 | 0x44c0000 | | |
| | 37 | blk.3.ffn_norm.weight | 0x62e84920 | 0x5000 | | |
| | 38 | blk.3.ffn_up.weight | 0x62e89920 | 0x44c0000 | | |
| | 39 | blk.4.attn_k.weight | 0x67349920 | 0x226000 | | |
| | 40 | blk.4.attn_norm.weight | 0x6756f920 | 0x5000 | | |
| | 41 | blk.4.attn_output.weight | 0x67574920 | 0xb40000 | | |
| | 42 | blk.4.attn_q.weight | 0x680b4920 | 0x898000 | | |
| | 43 | blk.4.attn_v.weight | 0x6894c920 | 0x2a8000 | | |
| | 44 | blk.4.ffn_down.weight | 0x68bf4920 | 0x5a00000 | | |
| | 45 | blk.4.ffn_gate.weight | 0x6e5f4920 | 0x44c0000 | | |
| | 46 | blk.4.ffn_norm.weight | 0x72ab4920 | 0x5000 | | |
| | 47 | blk.4.ffn_up.weight | 0x72ab9920 | 0x44c0000 | | |
| | 48 | blk.5.attn_k.weight | 0x76f79920 | 0x226000 | | |
| | 49 | blk.5.attn_norm.weight | 0x7719f920 | 0x5000 | | |
| | 50 | blk.5.attn_output.weight | 0x771a4920 | 0xb40000 | | |
| | 51 | blk.5.attn_q.weight | 0x77ce4920 | 0x898000 | | |
| | 52 | blk.5.attn_v.weight | 0x7857c920 | 0x2a8000 | | |
| | 53 | blk.5.ffn_down.weight | 0x78824920 | 0x5a00000 | | |
| | 54 | blk.5.ffn_gate.weight | 0x7e224920 | 0x44c0000 | | |
| | 55 | blk.5.ffn_norm.weight | 0x826e4920 | 0x5000 | | |
| | 56 | blk.5.ffn_up.weight | 0x826e9920 | 0x44c0000 | | |
| | 57 | blk.6.attn_k.weight | 0x86ba9920 | 0x226000 | | |
| | 58 | blk.6.attn_norm.weight | 0x86dcf920 | 0x5000 | | |
| | 59 | blk.6.attn_output.weight | 0x86dd4920 | 0xb40000 | | |
| | 60 | blk.6.attn_q.weight | 0x87914920 | 0x898000 | | |
| | 61 | blk.6.attn_v.weight | 0x881ac920 | 0x2a8000 | | |
| | 62 | blk.6.ffn_down.weight | 0x88454920 | 0x5a00000 | | |
| | 63 | blk.6.ffn_gate.weight | 0x8de54920 | 0x44c0000 | | |
| | 64 | blk.6.ffn_norm.weight | 0x92314920 | 0x5000 | | |
| | 65 | blk.6.ffn_up.weight | 0x92319920 | 0x44c0000 | | |
| | 66 | blk.7.attn_k.weight | 0x967d9920 | 0x226000 | | |
| | 67 | blk.7.attn_norm.weight | 0x969ff920 | 0x5000 | | |
| | 68 | blk.7.attn_output.weight | 0x96a04920 | 0xb40000 | | |
| | 69 | blk.7.attn_q.weight | 0x97544920 | 0x898000 | | |
| | 70 | blk.7.attn_v.weight | 0x97ddc920 | 0x2a8000 | | |
| | 71 | blk.7.ffn_down.weight | 0x98084920 | 0x5a00000 | | |
| | 72 | blk.7.ffn_gate.weight | 0x9da84920 | 0x44c0000 | | |
| | 73 | blk.7.ffn_norm.weight | 0xa1f44920 | 0x5000 | | |
| | 74 | blk.7.ffn_up.weight | 0xa1f49920 | 0x44c0000 | | |
| | 75 | blk.8.attn_k.weight | 0xa6409920 | 0x226000 | | |
| | 76 | blk.8.attn_norm.weight | 0xa662f920 | 0x5000 | | |
| | 77 | blk.8.attn_output.weight | 0xa6634920 | 0xb40000 | | |
| | 78 | blk.8.attn_q.weight | 0xa7174920 | 0x898000 | | |
| | 79 | blk.8.attn_v.weight | 0xa7a0c920 | 0x2a8000 | | |
| | 80 | blk.8.ffn_down.weight | 0xa7cb4920 | 0x5a00000 | | |
| | 81 | blk.8.ffn_gate.weight | 0xad6b4920 | 0x44c0000 | | |
| | 82 | blk.8.ffn_norm.weight | 0xb1b74920 | 0x5000 | | |
| | 83 | blk.8.ffn_up.weight | 0xb1b79920 | 0x44c0000 | | |
| | 84 | blk.9.attn_k.weight | 0xb6039920 | 0x226000 | | |
| | 85 | blk.9.attn_norm.weight | 0xb625f920 | 0x5000 | | |
| | 86 | blk.9.attn_output.weight | 0xb6264920 | 0xb40000 | | |
| | 87 | blk.9.attn_q.weight | 0xb6da4920 | 0x898000 | | |
| | 88 | blk.9.attn_v.weight | 0xb763c920 | 0x2a8000 | | |
| | 89 | blk.9.ffn_down.weight | 0xb78e4920 | 0x5a00000 | | |
| | 90 | blk.9.ffn_gate.weight | 0xbd2e4920 | 0x44c0000 | | |
| | 91 | blk.9.ffn_norm.weight | 0xc17a4920 | 0x5000 | | |
| | 92 | blk.9.ffn_up.weight | 0xc17a9920 | 0x44c0000 | | |
| | 93 | blk.10.attn_k.weight | 0xc5c69920 | 0x226000 | | |
| | 94 | blk.10.attn_norm.weight | 0xc5e8f920 | 0x5000 | | |
| | 95 | blk.10.attn_output.weight | 0xc5e94920 | 0xb40000 | | |
| | 96 | blk.10.attn_q.weight | 0xc69d4920 | 0x898000 | | |
| | 97 | blk.10.attn_v.weight | 0xc726c920 | 0x2a8000 | | |
| | 98 | blk.10.ffn_down.weight | 0xc7514920 | 0x5a00000 | | |
| | 99 | blk.10.ffn_gate.weight | 0xccf14920 | 0x44c0000 | | |
| | 100 | blk.10.ffn_norm.weight | 0xd13d4920 | 0x5000 | | |
| | 101 | blk.10.ffn_up.weight | 0xd13d9920 | 0x44c0000 | | |
| | 102 | blk.11.attn_k.weight | 0xd5899920 | 0x226000 | | |
| | 103 | blk.11.attn_norm.weight | 0xd5abf920 | 0x5000 | | |
| | 104 | blk.11.attn_output.weight | 0xd5ac4920 | 0xb40000 | | |
| | 105 | blk.11.attn_q.weight | 0xd6604920 | 0x898000 | | |
| | 106 | blk.11.attn_v.weight | 0xd6e9c920 | 0x2a8000 | | |
| | 107 | blk.11.ffn_down.weight | 0xd7144920 | 0x5a00000 | | |
| | 108 | blk.11.ffn_gate.weight | 0xdcb44920 | 0x44c0000 | | |
| | 109 | blk.11.ffn_norm.weight | 0xe1004920 | 0x5000 | | |
| | 110 | blk.11.ffn_up.weight | 0xe1009920 | 0x44c0000 | | |
| | 111 | blk.12.attn_k.weight | 0xe54c9920 | 0x226000 | | |
| | 112 | blk.12.attn_norm.weight | 0xe56ef920 | 0x5000 | | |
| | 113 | blk.12.attn_output.weight | 0xe56f4920 | 0xb40000 | | |
| | 114 | blk.12.attn_q.weight | 0xe6234920 | 0x898000 | | |
| | 115 | blk.12.attn_v.weight | 0xe6acc920 | 0x2a8000 | | |
| | 116 | blk.12.ffn_down.weight | 0xe6d74920 | 0x5a00000 | | |
| | 117 | blk.12.ffn_gate.weight | 0xec774920 | 0x44c0000 | | |
| | 118 | blk.12.ffn_norm.weight | 0xf0c34920 | 0x5000 | | |
| | 119 | blk.12.ffn_up.weight | 0xf0c39920 | 0x44c0000 | | |
| | 120 | blk.13.attn_k.weight | 0xf50f9920 | 0x226000 | | |
| | 121 | blk.13.attn_norm.weight | 0xf531f920 | 0x5000 | | |
| | 122 | blk.13.attn_output.weight | 0xf5324920 | 0xb40000 | | |
| | 123 | blk.13.attn_q.weight | 0xf5e64920 | 0x898000 | | |
| | 124 | blk.13.attn_v.weight | 0xf66fc920 | 0x2a8000 | | |
| | 125 | blk.13.ffn_down.weight | 0xf69a4920 | 0x5a00000 | | |
| | 126 | blk.13.ffn_gate.weight | 0xfc3a4920 | 0x44c0000 | | |
| | 127 | blk.13.ffn_norm.weight | 0x100864920 | 0x5000 | | |
| | 128 | blk.13.ffn_up.weight | 0x100869920 | 0x44c0000 | | |
| | 129 | blk.14.attn_k.weight | 0x104d29920 | 0x226000 | | |
| | 130 | blk.14.attn_norm.weight | 0x104f4f920 | 0x5000 | | |
| | 131 | blk.14.attn_output.weight | 0x104f54920 | 0xb40000 | | |
| | 132 | blk.14.attn_q.weight | 0x105a94920 | 0x898000 | | |
| | 133 | blk.14.attn_v.weight | 0x10632c920 | 0x2a8000 | | |
| | 134 | blk.14.ffn_down.weight | 0x1065d4920 | 0x5a00000 | | |
| | 135 | blk.14.ffn_gate.weight | 0x10bfd4920 | 0x44c0000 | | |
| | 136 | blk.14.ffn_norm.weight | 0x110494920 | 0x5000 | | |
| | 137 | blk.14.ffn_up.weight | 0x110499920 | 0x44c0000 | | |
| | 138 | blk.15.attn_k.weight | 0x114959920 | 0x226000 | | |
| | 139 | blk.15.attn_norm.weight | 0x114b7f920 | 0x5000 | | |
| | 140 | blk.15.attn_output.weight | 0x114b84920 | 0xb40000 | | |
| | 141 | blk.15.attn_q.weight | 0x1156c4920 | 0x898000 | | |
| | 142 | blk.15.attn_v.weight | 0x115f5c920 | 0x2a8000 | | |
| | 143 | blk.15.ffn_down.weight | 0x116204920 | 0x5a00000 | | |
| | 144 | blk.15.ffn_gate.weight | 0x11bc04920 | 0x44c0000 | | |
| | 145 | blk.15.ffn_norm.weight | 0x1200c4920 | 0x5000 | | |
| | 146 | blk.15.ffn_up.weight | 0x1200c9920 | 0x44c0000 | | |
| | 147 | blk.16.attn_k.weight | 0x124589920 | 0x226000 | | |
| | 148 | blk.16.attn_norm.weight | 0x1247af920 | 0x5000 | | |
| | 149 | blk.16.attn_output.weight | 0x1247b4920 | 0xb40000 | | |
| | 150 | blk.16.attn_q.weight | 0x1252f4920 | 0x898000 | | |
| | 151 | blk.16.attn_v.weight | 0x125b8c920 | 0x2a8000 | | |
| | 152 | blk.16.ffn_down.weight | 0x125e34920 | 0x5a00000 | | |
| | 153 | blk.16.ffn_gate.weight | 0x12b834920 | 0x44c0000 | | |
| | 154 | blk.16.ffn_norm.weight | 0x12fcf4920 | 0x5000 | | |
| | 155 | blk.16.ffn_up.weight | 0x12fcf9920 | 0x44c0000 | | |
| | 156 | blk.17.attn_k.weight | 0x1341b9920 | 0x2d0000 | | |
| | 157 | blk.17.attn_norm.weight | 0x134489920 | 0x5000 | | |
| | 158 | blk.17.attn_output.weight | 0x13448e920 | 0xb40000 | | |
| | 159 | blk.17.attn_q.weight | 0x134fce920 | 0xb40000 | | |
| | 160 | blk.17.attn_v.weight | 0x135b0e920 | 0x2d0000 | | |
| | 161 | blk.17.ffn_down.weight | 0x135dde920 | 0x5a00000 | | |
| | 162 | blk.17.ffn_gate.weight | 0x13b7de920 | 0x44c0000 | | |
| | 163 | blk.17.ffn_norm.weight | 0x13fc9e920 | 0x5000 | | |
| | 164 | blk.17.ffn_up.weight | 0x13fca3920 | 0x44c0000 | | |
| | 165 | blk.18.attn_k.weight | 0x144163920 | 0x2d0000 | | |
| | 166 | blk.18.attn_norm.weight | 0x144433920 | 0x5000 | | |
| | 167 | blk.18.attn_output.weight | 0x144438920 | 0xb40000 | | |
| | 168 | blk.18.attn_q.weight | 0x144f78920 | 0xb40000 | | |
| | 169 | blk.18.attn_v.weight | 0x145ab8920 | 0x2d0000 | | |
| | 170 | blk.18.ffn_down.weight | 0x145d88920 | 0x5a00000 | | |
| | 171 | blk.18.ffn_gate.weight | 0x14b788920 | 0x44c0000 | | |
| | 172 | blk.18.ffn_norm.weight | 0x14fc48920 | 0x5000 | | |
| | 173 | blk.18.ffn_up.weight | 0x14fc4d920 | 0x44c0000 | | |
| | 174 | blk.19.attn_k.weight | 0x15410d920 | 0x226000 | | |
| | 175 | blk.19.attn_norm.weight | 0x154333920 | 0x5000 | | |
| | 176 | blk.19.attn_output.weight | 0x154338920 | 0xb40000 | | |
| | 177 | blk.19.attn_q.weight | 0x154e78920 | 0x898000 | | |
| | 178 | blk.19.attn_v.weight | 0x155710920 | 0x2a8000 | | |
| | 179 | blk.19.ffn_down.weight | 0x1559b8920 | 0x5a00000 | | |
| | 180 | blk.19.ffn_gate.weight | 0x15b3b8920 | 0x44c0000 | | |
| | 181 | blk.19.ffn_norm.weight | 0x15f878920 | 0x5000 | | |
| | 182 | blk.19.ffn_up.weight | 0x15f87d920 | 0x44c0000 | | |
| | 183 | blk.20.attn_k.weight | 0x163d3d920 | 0x2d0000 | | |
| | 184 | blk.20.attn_norm.weight | 0x16400d920 | 0x5000 | | |
| | 185 | blk.20.attn_output.weight | 0x164012920 | 0xb40000 | | |
| | 186 | blk.20.attn_q.weight | 0x164b52920 | 0xb40000 | | |
| | 187 | blk.20.attn_v.weight | 0x165692920 | 0x2d0000 | | |
| | 188 | blk.20.ffn_down.weight | 0x165962920 | 0x5a00000 | | |
| | 189 | blk.20.ffn_gate.weight | 0x16b362920 | 0x5a00000 | | |
| | 190 | blk.20.ffn_norm.weight | 0x170d62920 | 0x5000 | | |
| | 191 | blk.20.ffn_up.weight | 0x170d67920 | 0x5a00000 | | |
| | 192 | blk.21.attn_k.weight | 0x176767920 | 0x226000 | | |
| | 193 | blk.21.attn_norm.weight | 0x17698d920 | 0x5000 | | |
| | 194 | blk.21.attn_output.weight | 0x176992920 | 0xb40000 | | |
| | 195 | blk.21.attn_q.weight | 0x1774d2920 | 0x898000 | | |
| | 196 | blk.21.attn_v.weight | 0x177d6a920 | 0x2a8000 | | |
| | 197 | blk.21.ffn_down.weight | 0x178012920 | 0x5a00000 | | |
| | 198 | blk.21.ffn_gate.weight | 0x17da12920 | 0x5a00000 | | |
| | 199 | blk.21.ffn_norm.weight | 0x183412920 | 0x5000 | | |
| | 200 | blk.21.ffn_up.weight | 0x183417920 | 0x5a00000 | | |
| | 201 | blk.22.attn_k.weight | 0x188e17920 | 0x2d0000 | | |
| | 202 | blk.22.attn_norm.weight | 0x1890e7920 | 0x5000 | | |
| | 203 | blk.22.attn_output.weight | 0x1890ec920 | 0xb40000 | | |
| | 204 | blk.22.attn_q.weight | 0x189c2c920 | 0xb40000 | | |
| | 205 | blk.22.attn_v.weight | 0x18a76c920 | 0x2d0000 | | |
| | 206 | blk.22.ffn_down.weight | 0x18aa3c920 | 0x5a00000 | | |
| | 207 | blk.22.ffn_gate.weight | 0x19043c920 | 0x5a00000 | | |
| | 208 | blk.22.ffn_norm.weight | 0x195e3c920 | 0x5000 | | |
| | 209 | blk.22.ffn_up.weight | 0x195e41920 | 0x5a00000 | | |
| | 210 | blk.23.attn_k.weight | 0x19b841920 | 0x2d0000 | | |
| | 211 | blk.23.attn_norm.weight | 0x19bb11920 | 0x5000 | | |
| | 212 | blk.23.attn_output.weight | 0x19bb16920 | 0xb40000 | | |
| | 213 | blk.23.attn_q.weight | 0x19c656920 | 0xb40000 | | |
| | 214 | blk.23.attn_v.weight | 0x19d196920 | 0x2d0000 | | |
| | 215 | blk.23.ffn_down.weight | 0x19d466920 | 0x5a00000 | | |
| | 216 | blk.23.ffn_gate.weight | 0x1a2e66920 | 0x5a00000 | | |
| | 217 | blk.23.ffn_norm.weight | 0x1a8866920 | 0x5000 | | |
| | 218 | blk.23.ffn_up.weight | 0x1a886b920 | 0x5a00000 | | |
| | 219 | blk.24.attn_k.weight | 0x1ae26b920 | 0x2d0000 | | |
| | 220 | blk.24.attn_norm.weight | 0x1ae53b920 | 0x5000 | | |
| | 221 | blk.24.attn_output.weight | 0x1ae540920 | 0xb40000 | | |
| | 222 | blk.24.attn_q.weight | 0x1af080920 | 0xb40000 | | |
| | 223 | blk.24.attn_v.weight | 0x1afbc0920 | 0x2d0000 | | |
| | 224 | blk.24.ffn_down.weight | 0x1afe90920 | 0x5a00000 | | |
| | 225 | blk.24.ffn_gate.weight | 0x1b5890920 | 0x5a00000 | | |
| | 226 | blk.24.ffn_norm.weight | 0x1bb290920 | 0x5000 | | |
| | 227 | blk.24.ffn_up.weight | 0x1bb295920 | 0x5a00000 | | |
| | 228 | blk.25.attn_k.weight | 0x1c0c95920 | 0x2d0000 | | |
| | 229 | blk.25.attn_norm.weight | 0x1c0f65920 | 0x5000 | | |
| | 230 | blk.25.attn_output.weight | 0x1c0f6a920 | 0xb40000 | | |
| | 231 | blk.25.attn_q.weight | 0x1c1aaa920 | 0xb40000 | | |
| | 232 | blk.25.attn_v.weight | 0x1c25ea920 | 0x2d0000 | | |
| | 233 | blk.25.ffn_down.weight | 0x1c28ba920 | 0x5a00000 | | |
| | 234 | blk.25.ffn_gate.weight | 0x1c82ba920 | 0x5a00000 | | |
| | 235 | blk.25.ffn_norm.weight | 0x1cdcba920 | 0x5000 | | |
| | 236 | blk.25.ffn_up.weight | 0x1cdcbf920 | 0x5a00000 | | |
| | 237 | blk.26.attn_k.weight | 0x1d36bf920 | 0x2d0000 | | |
| | 238 | blk.26.attn_norm.weight | 0x1d398f920 | 0x5000 | | |
| | 239 | blk.26.attn_output.weight | 0x1d3994920 | 0xb40000 | | |
| | 240 | blk.26.attn_q.weight | 0x1d44d4920 | 0xb40000 | | |
| | 241 | blk.26.attn_v.weight | 0x1d5014920 | 0x2d0000 | | |
| | 242 | blk.26.ffn_down.weight | 0x1d52e4920 | 0x5a00000 | | |
| | 243 | blk.26.ffn_gate.weight | 0x1dace4920 | 0x5a00000 | | |
| | 244 | blk.26.ffn_norm.weight | 0x1e06e4920 | 0x5000 | | |
| | 245 | blk.26.ffn_up.weight | 0x1e06e9920 | 0x5a00000 | | |
| | 246 | blk.27.attn_k.weight | 0x1e60e9920 | 0x226000 | | |
| | 247 | blk.27.attn_norm.weight | 0x1e630f920 | 0x5000 | | |
| | 248 | blk.27.attn_output.weight | 0x1e6314920 | 0xb40000 | | |
| | 249 | blk.27.attn_q.weight | 0x1e6e54920 | 0x898000 | | |
| | 250 | blk.27.attn_v.weight | 0x1e76ec920 | 0x2a8000 | | |
| | 251 | blk.27.ffn_down.weight | 0x1e7994920 | 0x5a00000 | | |
| | 252 | blk.27.ffn_gate.weight | 0x1ed394920 | 0x5a00000 | | |
| | 253 | blk.27.ffn_norm.weight | 0x1f2d94920 | 0x5000 | | |
| | 254 | blk.27.ffn_up.weight | 0x1f2d99920 | 0x5a00000 | | |
| | 255 | blk.28.attn_k.weight | 0x1f8799920 | 0x2d0000 | | |
| | 256 | blk.28.attn_norm.weight | 0x1f8a69920 | 0x5000 | | |
| | 257 | blk.28.attn_output.weight | 0x1f8a6e920 | 0xb40000 | | |
| | 258 | blk.28.attn_q.weight | 0x1f95ae920 | 0xb40000 | | |
| | 259 | blk.28.attn_v.weight | 0x1fa0ee920 | 0x2d0000 | | |
| | 260 | blk.28.ffn_down.weight | 0x1fa3be920 | 0x5a00000 | | |
| | 261 | blk.28.ffn_gate.weight | 0x1ffdbe920 | 0x5a00000 | | |
| | 262 | blk.28.ffn_norm.weight | 0x2057be920 | 0x5000 | | |
| | 263 | blk.28.ffn_up.weight | 0x2057c3920 | 0x5a00000 | | |
| | 264 | blk.29.attn_k.weight | 0x20b1c3920 | 0x2d0000 | | |
| | 265 | blk.29.attn_norm.weight | 0x20b493920 | 0x5000 | | |
| | 266 | blk.29.attn_output.weight | 0x20b498920 | 0xb40000 | | |
| | 267 | blk.29.attn_q.weight | 0x20bfd8920 | 0xb40000 | | |
| | 268 | blk.29.attn_v.weight | 0x20cb18920 | 0x2d0000 | | |
| | 269 | blk.29.ffn_down.weight | 0x20cde8920 | 0x5a00000 | | |
| | 270 | blk.29.ffn_gate.weight | 0x2127e8920 | 0x5a00000 | | |
| | 271 | blk.29.ffn_norm.weight | 0x2181e8920 | 0x5000 | | |
| | 272 | blk.29.ffn_up.weight | 0x2181ed920 | 0x5a00000 | | |
| | 273 | blk.30.attn_k.weight | 0x21dbed920 | 0x2d0000 | | |
| | 274 | blk.30.attn_norm.weight | 0x21debd920 | 0x5000 | | |
| | 275 | blk.30.attn_output.weight | 0x21dec2920 | 0xb40000 | | |
| | 276 | blk.30.attn_q.weight | 0x21ea02920 | 0xb40000 | | |
| | 277 | blk.30.attn_v.weight | 0x21f542920 | 0x2d0000 | | |
| | 278 | blk.30.ffn_down.weight | 0x21f812920 | 0x5a00000 | | |
| | 279 | blk.30.ffn_gate.weight | 0x225212920 | 0x5a00000 | | |
| | 280 | blk.30.ffn_norm.weight | 0x22ac12920 | 0x5000 | | |
| | 281 | blk.30.ffn_up.weight | 0x22ac17920 | 0x5a00000 | | |
| | 282 | blk.31.attn_k.weight | 0x230617920 | 0x2d0000 | | |
| | 283 | blk.31.attn_norm.weight | 0x2308e7920 | 0x5000 | | |
| | 284 | blk.31.attn_output.weight | 0x2308ec920 | 0xb40000 | | |
| | 285 | blk.31.attn_q.weight | 0x23142c920 | 0xb40000 | | |
| | 286 | blk.31.attn_v.weight | 0x231f6c920 | 0x2d0000 | | |
| | 287 | blk.31.ffn_down.weight | 0x23223c920 | 0x5a00000 | | |
| | 288 | blk.31.ffn_gate.weight | 0x237c3c920 | 0x5a00000 | | |
| | 289 | blk.31.ffn_norm.weight | 0x23d63c920 | 0x5000 | | |
| | 290 | blk.31.ffn_up.weight | 0x23d641920 | 0x5a00000 | | |
| | 291 | blk.32.attn_k.weight | 0x243041920 | 0x2d0000 | | |
| | 292 | blk.32.attn_norm.weight | 0x243311920 | 0x5000 | | |
| | 293 | blk.32.attn_output.weight | 0x243316920 | 0xb40000 | | |
| | 294 | blk.32.attn_q.weight | 0x243e56920 | 0xb40000 | | |
| | 295 | blk.32.attn_v.weight | 0x244996920 | 0x2d0000 | | |
| | 296 | blk.32.ffn_down.weight | 0x244c66920 | 0x5a00000 | | |
| | 297 | blk.32.ffn_gate.weight | 0x24a666920 | 0x5a00000 | | |
| | 298 | blk.32.ffn_norm.weight | 0x250066920 | 0x5000 | | |
| | 299 | blk.32.ffn_up.weight | 0x25006b920 | 0x5a00000 | | |
| | 300 | blk.33.attn_k.weight | 0x255a6b920 | 0x2d0000 | | |
| | 301 | blk.33.attn_norm.weight | 0x255d3b920 | 0x5000 | | |
| | 302 | blk.33.attn_output.weight | 0x255d40920 | 0xb40000 | | |
| | 303 | blk.33.attn_q.weight | 0x256880920 | 0xb40000 | | |
| | 304 | blk.33.attn_v.weight | 0x2573c0920 | 0x2d0000 | | |
| | 305 | blk.33.ffn_down.weight | 0x257690920 | 0x5a00000 | | |
| | 306 | blk.33.ffn_gate.weight | 0x25d090920 | 0x5a00000 | | |
| | 307 | blk.33.ffn_norm.weight | 0x262a90920 | 0x5000 | | |
| | 308 | blk.33.ffn_up.weight | 0x262a95920 | 0x5a00000 | | |
| | 309 | blk.34.attn_k.weight | 0x268495920 | 0x2d0000 | | |
| | 310 | blk.34.attn_norm.weight | 0x268765920 | 0x5000 | | |
| | 311 | blk.34.attn_output.weight | 0x26876a920 | 0xb40000 | | |
| | 312 | blk.34.attn_q.weight | 0x2692aa920 | 0xb40000 | | |
| | 313 | blk.34.attn_v.weight | 0x269dea920 | 0x2d0000 | | |
| | 314 | blk.34.ffn_down.weight | 0x26a0ba920 | 0x5a00000 | | |
| | 315 | blk.34.ffn_gate.weight | 0x26faba920 | 0x5a00000 | | |
| | 316 | blk.34.ffn_norm.weight | 0x2754ba920 | 0x5000 | | |
| | 317 | blk.34.ffn_up.weight | 0x2754bf920 | 0x5a00000 | | |
| | 318 | blk.35.attn_k.weight | 0x27aebf920 | 0x2d0000 | | |
| | 319 | blk.35.attn_norm.weight | 0x27b18f920 | 0x5000 | | |
| | 320 | blk.35.attn_output.weight | 0x27b194920 | 0xb40000 | | |
| | 321 | blk.35.attn_q.weight | 0x27bcd4920 | 0xb40000 | | |
| | 322 | blk.35.attn_v.weight | 0x27c814920 | 0x2d0000 | | |
| | 323 | blk.35.ffn_down.weight | 0x27cae4920 | 0x5a00000 | | |
| | 324 | blk.35.ffn_gate.weight | 0x2824e4920 | 0x5a00000 | | |
| | 325 | blk.35.ffn_norm.weight | 0x287ee4920 | 0x5000 | | |
| | 326 | blk.35.ffn_up.weight | 0x287ee9920 | 0x5a00000 | | |
| | 327 | blk.36.attn_k.weight | 0x28d8e9920 | 0x2d0000 | | |
| | 328 | blk.36.attn_norm.weight | 0x28dbb9920 | 0x5000 | | |
| | 329 | blk.36.attn_output.weight | 0x28dbbe920 | 0xb40000 | | |
| | 330 | blk.36.attn_q.weight | 0x28e6fe920 | 0xb40000 | | |
| | 331 | blk.36.attn_v.weight | 0x28f23e920 | 0x2d0000 | | |
| | 332 | blk.36.ffn_down.weight | 0x28f50e920 | 0x5a00000 | | |
| | 333 | blk.36.ffn_gate.weight | 0x294f0e920 | 0x5a00000 | | |
| | 334 | blk.36.ffn_norm.weight | 0x29a90e920 | 0x5000 | | |
| | 335 | blk.36.ffn_up.weight | 0x29a913920 | 0x5a00000 | | |
| | 336 | blk.37.attn_k.weight | 0x2a0313920 | 0x2d0000 | | |
| | 337 | blk.37.attn_norm.weight | 0x2a05e3920 | 0x5000 | | |
| | 338 | blk.37.attn_output.weight | 0x2a05e8920 | 0xb40000 | | |
| | 339 | blk.37.attn_q.weight | 0x2a1128920 | 0xb40000 | | |
| | 340 | blk.37.attn_v.weight | 0x2a1c68920 | 0x2d0000 | | |
| | 341 | blk.37.ffn_down.weight | 0x2a1f38920 | 0x5a00000 | | |
| | 342 | blk.37.ffn_gate.weight | 0x2a7938920 | 0x5a00000 | | |
| | 343 | blk.37.ffn_norm.weight | 0x2ad338920 | 0x5000 | | |
| | 344 | blk.37.ffn_up.weight | 0x2ad33d920 | 0x5a00000 | | |
| | 345 | blk.38.attn_k.weight | 0x2b2d3d920 | 0x2d0000 | | |
| | 346 | blk.38.attn_norm.weight | 0x2b300d920 | 0x5000 | | |
| | 347 | blk.38.attn_output.weight | 0x2b3012920 | 0xb40000 | | |
| | 348 | blk.38.attn_q.weight | 0x2b3b52920 | 0xb40000 | | |
| | 349 | blk.38.attn_v.weight | 0x2b4692920 | 0x2d0000 | | |
| | 350 | blk.38.ffn_down.weight | 0x2b4962920 | 0x5a00000 | | |
| | 351 | blk.38.ffn_gate.weight | 0x2ba362920 | 0x5a00000 | | |
| | 352 | blk.38.ffn_norm.weight | 0x2bfd62920 | 0x5000 | | |
| | 353 | blk.38.ffn_up.weight | 0x2bfd67920 | 0x5a00000 | | |
| | 354 | blk.39.attn_k.weight | 0x2c5767920 | 0x2d0000 | | |
| | 355 | blk.39.attn_norm.weight | 0x2c5a37920 | 0x5000 | | |
| | 356 | blk.39.attn_output.weight | 0x2c5a3c920 | 0xb40000 | | |
| | 357 | blk.39.attn_q.weight | 0x2c657c920 | 0xb40000 | | |
| | 358 | blk.39.attn_v.weight | 0x2c70bc920 | 0x2d0000 | | |
| | 359 | blk.39.ffn_down.weight | 0x2c738c920 | 0x5a00000 | | |
| | 360 | blk.39.ffn_gate.weight | 0x2ccd8c920 | 0x5a00000 | | |
| | 361 | blk.39.ffn_norm.weight | 0x2d278c920 | 0x5000 | | |
| | 362 | blk.39.ffn_up.weight | 0x2d2791920 | 0x5a00000 | | |
| ### <a name="base">Base Tensor Group : ~1B Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-------| | |
| | 0 | output.weight | Output (W) | (~671M) 671088640 | 5120 x 131072 x 1 x 1 | IQ4_NL | | |
| | 1 | output_norm.weight | Output Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 2 | token_embd.weight | Token Embedding (W) | (~671M) 671088640 | 5120 x 131072 x 1 x 1 | IQ3_S | | |
| - Total elements in base: ( ~1B) 1342182400 | |
| - Percentage of total elements: 5.69% | |
| ### <a name="blk_0">Block 0 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-------| | |
| | 3 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 4 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 5 | blk.0.attn_output.weight | Block 0 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 6 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 7 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 8 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 9 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 10 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 11 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.0: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_1">Block 1 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-------| | |
| | 12 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 13 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 14 | blk.1.attn_output.weight | Block 1 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 15 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 16 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 17 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 18 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 19 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 20 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.1: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_2">Block 2 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-------| | |
| | 21 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 22 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 23 | blk.2.attn_output.weight | Block 2 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 24 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 25 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 26 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 27 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 28 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 29 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.2: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_3">Block 3 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-------| | |
| | 30 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 31 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 32 | blk.3.attn_output.weight | Block 3 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 33 | blk.3.attn_q.weight | Block 3 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 34 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 35 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 36 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 37 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 38 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.3: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_4">Block 4 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-------| | |
| | 39 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 40 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 41 | blk.4.attn_output.weight | Block 4 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 42 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 43 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 44 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 45 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 46 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 47 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.4: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_5">Block 5 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-------| | |
| | 48 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 49 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 50 | blk.5.attn_output.weight | Block 5 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 51 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 52 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 53 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 54 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 55 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 56 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.5: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_6">Block 6 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-------| | |
| | 57 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 58 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 59 | blk.6.attn_output.weight | Block 6 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 60 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 61 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 62 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 63 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 64 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 65 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.6: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_7">Block 7 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-------| | |
| | 66 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 67 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 68 | blk.7.attn_output.weight | Block 7 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 69 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 70 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 71 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 72 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 73 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 74 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.7: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_8">Block 8 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-------| | |
| | 75 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 76 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 77 | blk.8.attn_output.weight | Block 8 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 78 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 79 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 80 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 81 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 82 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 83 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.8: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_9">Block 9 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-------| | |
| | 84 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 85 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 86 | blk.9.attn_output.weight | Block 9 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 87 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 88 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 89 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 90 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 91 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 92 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.9: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_10">Block 10 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 93 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 94 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 95 | blk.10.attn_output.weight | Block 10 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 96 | blk.10.attn_q.weight | Block 10 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 97 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 98 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 99 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 100 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 101 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.10: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_11">Block 11 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 102 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 103 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 104 | blk.11.attn_output.weight | Block 11 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 105 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 106 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 107 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 108 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 109 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 110 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.11: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_12">Block 12 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 111 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 112 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 113 | blk.12.attn_output.weight | Block 12 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 114 | blk.12.attn_q.weight | Block 12 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 115 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 116 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 117 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 118 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 119 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.12: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_13">Block 13 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 120 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 121 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 122 | blk.13.attn_output.weight | Block 13 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 123 | blk.13.attn_q.weight | Block 13 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 124 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 125 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 126 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 127 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 128 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.13: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_14">Block 14 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 129 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 130 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 131 | blk.14.attn_output.weight | Block 14 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 132 | blk.14.attn_q.weight | Block 14 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 133 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 134 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 135 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 136 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 137 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.14: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_15">Block 15 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 138 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 139 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 140 | blk.15.attn_output.weight | Block 15 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 141 | blk.15.attn_q.weight | Block 15 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 142 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 143 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 144 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 145 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 146 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.15: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_16">Block 16 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 147 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 148 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 149 | blk.16.attn_output.weight | Block 16 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 150 | blk.16.attn_q.weight | Block 16 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 151 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 152 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 153 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 154 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 155 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.16: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_17">Block 17 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 156 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 157 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 158 | blk.17.attn_output.weight | Block 17 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 159 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 160 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 161 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 162 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 163 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 164 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.17: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_18">Block 18 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 165 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 166 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 167 | blk.18.attn_output.weight | Block 18 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 168 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 169 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 170 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 171 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 172 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 173 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.18: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_19">Block 19 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 174 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 175 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 176 | blk.19.attn_output.weight | Block 19 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 177 | blk.19.attn_q.weight | Block 19 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 178 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 179 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 180 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| | 181 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 182 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ3_S | | |
| - Total elements in blk.19: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_20">Block 20 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 183 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 184 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 185 | blk.20.attn_output.weight | Block 20 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 186 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 187 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 188 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 189 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 190 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 191 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.20: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_21">Block 21 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 192 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 193 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 194 | blk.21.attn_output.weight | Block 21 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 195 | blk.21.attn_q.weight | Block 21 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 196 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 197 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 198 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 199 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 200 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.21: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_22">Block 22 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 201 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 202 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 203 | blk.22.attn_output.weight | Block 22 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 204 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 205 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 206 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 207 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 208 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 209 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.22: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_23">Block 23 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 210 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 211 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 212 | blk.23.attn_output.weight | Block 23 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 213 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 214 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 215 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 216 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 217 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 218 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.23: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_24">Block 24 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 219 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 220 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 221 | blk.24.attn_output.weight | Block 24 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 222 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 223 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 224 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 225 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 226 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 227 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.24: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_25">Block 25 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 228 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 229 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 230 | blk.25.attn_output.weight | Block 25 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 231 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 232 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 233 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 234 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 235 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 236 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.25: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_26">Block 26 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 237 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 238 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 239 | blk.26.attn_output.weight | Block 26 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 240 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 241 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 242 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 243 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 244 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 245 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.26: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_27">Block 27 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 246 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ3_S | | |
| | 247 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 248 | blk.27.attn_output.weight | Block 27 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 249 | blk.27.attn_q.weight | Block 27 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ3_S | | |
| | 250 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_XS | | |
| | 251 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 252 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 253 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 254 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.27: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_28">Block 28 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 255 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 256 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 257 | blk.28.attn_output.weight | Block 28 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 258 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 259 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 260 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 261 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 262 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 263 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.28: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_29">Block 29 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 264 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 265 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 266 | blk.29.attn_output.weight | Block 29 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 267 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 268 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 269 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 270 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 271 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 272 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.29: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_30">Block 30 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 273 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 274 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 275 | blk.30.attn_output.weight | Block 30 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 276 | blk.30.attn_q.weight | Block 30 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 277 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 278 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 279 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 280 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 281 | blk.30.ffn_up.weight | Block 30 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.30: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_31">Block 31 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 282 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 283 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 284 | blk.31.attn_output.weight | Block 31 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 285 | blk.31.attn_q.weight | Block 31 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 286 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 287 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 288 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 289 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 290 | blk.31.ffn_up.weight | Block 31 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.31: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_32">Block 32 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 291 | blk.32.attn_k.weight | Block 32 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 292 | blk.32.attn_norm.weight | Block 32 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 293 | blk.32.attn_output.weight | Block 32 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 294 | blk.32.attn_q.weight | Block 32 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 295 | blk.32.attn_v.weight | Block 32 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 296 | blk.32.ffn_down.weight | Block 32 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 297 | blk.32.ffn_gate.weight | Block 32 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 298 | blk.32.ffn_norm.weight | Block 32 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 299 | blk.32.ffn_up.weight | Block 32 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.32: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_33">Block 33 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 300 | blk.33.attn_k.weight | Block 33 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 301 | blk.33.attn_norm.weight | Block 33 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 302 | blk.33.attn_output.weight | Block 33 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 303 | blk.33.attn_q.weight | Block 33 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 304 | blk.33.attn_v.weight | Block 33 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 305 | blk.33.ffn_down.weight | Block 33 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 306 | blk.33.ffn_gate.weight | Block 33 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 307 | blk.33.ffn_norm.weight | Block 33 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 308 | blk.33.ffn_up.weight | Block 33 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.33: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_34">Block 34 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 309 | blk.34.attn_k.weight | Block 34 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 310 | blk.34.attn_norm.weight | Block 34 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 311 | blk.34.attn_output.weight | Block 34 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 312 | blk.34.attn_q.weight | Block 34 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 313 | blk.34.attn_v.weight | Block 34 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 314 | blk.34.ffn_down.weight | Block 34 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 315 | blk.34.ffn_gate.weight | Block 34 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 316 | blk.34.ffn_norm.weight | Block 34 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 317 | blk.34.ffn_up.weight | Block 34 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.34: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_35">Block 35 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 318 | blk.35.attn_k.weight | Block 35 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 319 | blk.35.attn_norm.weight | Block 35 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 320 | blk.35.attn_output.weight | Block 35 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 321 | blk.35.attn_q.weight | Block 35 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 322 | blk.35.attn_v.weight | Block 35 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 323 | blk.35.ffn_down.weight | Block 35 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 324 | blk.35.ffn_gate.weight | Block 35 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 325 | blk.35.ffn_norm.weight | Block 35 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 326 | blk.35.ffn_up.weight | Block 35 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.35: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_36">Block 36 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 327 | blk.36.attn_k.weight | Block 36 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 328 | blk.36.attn_norm.weight | Block 36 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 329 | blk.36.attn_output.weight | Block 36 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 330 | blk.36.attn_q.weight | Block 36 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 331 | blk.36.attn_v.weight | Block 36 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 332 | blk.36.ffn_down.weight | Block 36 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 333 | blk.36.ffn_gate.weight | Block 36 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 334 | blk.36.ffn_norm.weight | Block 36 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 335 | blk.36.ffn_up.weight | Block 36 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.36: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_37">Block 37 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 336 | blk.37.attn_k.weight | Block 37 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 337 | blk.37.attn_norm.weight | Block 37 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 338 | blk.37.attn_output.weight | Block 37 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 339 | blk.37.attn_q.weight | Block 37 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 340 | blk.37.attn_v.weight | Block 37 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 341 | blk.37.ffn_down.weight | Block 37 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 342 | blk.37.ffn_gate.weight | Block 37 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 343 | blk.37.ffn_norm.weight | Block 37 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 344 | blk.37.ffn_up.weight | Block 37 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.37: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_38">Block 38 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 345 | blk.38.attn_k.weight | Block 38 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 346 | blk.38.attn_norm.weight | Block 38 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 347 | blk.38.attn_output.weight | Block 38 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 348 | blk.38.attn_q.weight | Block 38 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 349 | blk.38.attn_v.weight | Block 38 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 350 | blk.38.ffn_down.weight | Block 38 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 351 | blk.38.ffn_gate.weight | Block 38 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 352 | blk.38.ffn_norm.weight | Block 38 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 353 | blk.38.ffn_up.weight | Block 38 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.38: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |
| ### <a name="blk_39">Block 39 Tensor Group : ~556M Elements</a> | |
| | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | | |
| |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-------| | |
| | 354 | blk.39.attn_k.weight | Block 39 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 355 | blk.39.attn_norm.weight | Block 39 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 356 | blk.39.attn_output.weight | Block 39 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | IQ4_NL | | |
| | 357 | blk.39.attn_q.weight | Block 39 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | IQ4_NL | | |
| | 358 | blk.39.attn_v.weight | Block 39 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | IQ4_NL | | |
| | 359 | blk.39.ffn_down.weight | Block 39 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | IQ4_NL | | |
| | 360 | blk.39.ffn_gate.weight | Block 39 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| | 361 | blk.39.ffn_norm.weight | Block 39 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | |
| | 362 | blk.39.ffn_up.weight | Block 39 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | IQ4_NL | | |
| - Total elements in blk.39: (~556M) 555755520 | |
| - Percentage of total elements: 2.36% | |