# Dolphin-Mistral-24B-Venice-Edition-F16.gguf - GGUF Internal File Dump - Endian: LITTLE endian ## Key Value Metadata Store There are 42 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 | 39 | | 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 | general.file_type | 1 | | 27 | UINT32 | 1 | llama.vocab_size | 131072 | | 28 | UINT32 | 1 | llama.rope.dimension_count | 128 | | 29 | UINT32 | 1 | general.quantization_version | 2 | | 30 | STRING | 1 | tokenizer.ggml.model | `gpt2` | | 31 | STRING | 1 | tokenizer.ggml.pre | `tekken` | | 32 | [STRING] | 131072 | tokenizer.ggml.tokens | [ ``, ``, ``, `[INST]`, `[/INST]`, ... ] | | 33 | [INT32] | 131072 | tokenizer.ggml.token_type | [ 3, 3, 3, 3, 3, 3, 3, ... ] | | 34 | [STRING] | 269443 | tokenizer.ggml.merges | [ `Ġ Ġ`, `Ġ t`, `e r`, `i n`, `Ġ ĠĠĠ`, ... ] | | 35 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 1 | | 36 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 2 | | 37 | UINT32 | 1 | tokenizer.ggml.unknown_token_id | 0 | | 38 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 11 | | 39 | BOOL | 1 | tokenizer.ggml.add_bos_token | True | | 40 | BOOL | 1 | tokenizer.ggml.add_eos_token | False | | 41 | STRING | 1 | tokenizer.chat_template | `{%- set today = strftime_now("`...` {%- endif %}{%- endfor %}` | | 42 | BOOL | 1 | tokenizer.ggml.add_space_prefix | False | ## Tensors Overview ~24B Elements Total number of elements in all tensors: 23572403200 Elements - [Dolphin-Mistral-24B-Venice-Edition-F16.gguf - GGUF Internal File Dump](#dolphin-mistral-24b-venice-edition-f16gguf---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 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 2 Tensor Group : ~556M Elements](#block-2-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 3 Tensor Group : ~556M Elements](#block-3-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) - [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) ### 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 | 0x784800 | 0x50000000 | | 1 | token_embd.weight | 0x50784800 | 0x50000000 | | 2 | blk.0.attn_norm.weight | 0xa0784800 | 0x5000 | | 3 | blk.0.ffn_down.weight | 0xa0789800 | 0x14000000 | | 4 | blk.0.ffn_gate.weight | 0xb4789800 | 0x14000000 | | 5 | blk.0.ffn_up.weight | 0xc8789800 | 0x14000000 | | 6 | blk.0.ffn_norm.weight | 0xdc789800 | 0x5000 | | 7 | blk.0.attn_k.weight | 0xdc78e800 | 0xa00000 | | 8 | blk.0.attn_output.weight | 0xdd18e800 | 0x2800000 | | 9 | blk.0.attn_q.weight | 0xdf98e800 | 0x2800000 | | 10 | blk.0.attn_v.weight | 0xe218e800 | 0xa00000 | | 11 | blk.1.attn_norm.weight | 0xe2b8e800 | 0x5000 | | 12 | blk.1.ffn_down.weight | 0xe2b93800 | 0x14000000 | | 13 | blk.1.ffn_gate.weight | 0xf6b93800 | 0x14000000 | | 14 | blk.1.ffn_up.weight | 0x10ab93800 | 0x14000000 | | 15 | blk.1.ffn_norm.weight | 0x11eb93800 | 0x5000 | | 16 | blk.1.attn_k.weight | 0x11eb98800 | 0xa00000 | | 17 | blk.1.attn_output.weight | 0x11f598800 | 0x2800000 | | 18 | blk.1.attn_q.weight | 0x121d98800 | 0x2800000 | | 19 | blk.1.attn_v.weight | 0x124598800 | 0xa00000 | | 20 | blk.10.attn_norm.weight | 0x124f98800 | 0x5000 | | 21 | blk.10.ffn_down.weight | 0x124f9d800 | 0x14000000 | | 22 | blk.10.ffn_gate.weight | 0x138f9d800 | 0x14000000 | | 23 | blk.10.ffn_up.weight | 0x14cf9d800 | 0x14000000 | | 24 | blk.10.ffn_norm.weight | 0x160f9d800 | 0x5000 | | 25 | blk.10.attn_k.weight | 0x160fa2800 | 0xa00000 | | 26 | blk.10.attn_output.weight | 0x1619a2800 | 0x2800000 | | 27 | blk.10.attn_q.weight | 0x1641a2800 | 0x2800000 | | 28 | blk.10.attn_v.weight | 0x1669a2800 | 0xa00000 | | 29 | blk.11.attn_norm.weight | 0x1673a2800 | 0x5000 | | 30 | blk.11.ffn_down.weight | 0x1673a7800 | 0x14000000 | | 31 | blk.11.ffn_gate.weight | 0x17b3a7800 | 0x14000000 | | 32 | blk.11.ffn_up.weight | 0x18f3a7800 | 0x14000000 | | 33 | blk.11.ffn_norm.weight | 0x1a33a7800 | 0x5000 | | 34 | blk.11.attn_k.weight | 0x1a33ac800 | 0xa00000 | | 35 | blk.11.attn_output.weight | 0x1a3dac800 | 0x2800000 | | 36 | blk.11.attn_q.weight | 0x1a65ac800 | 0x2800000 | | 37 | blk.11.attn_v.weight | 0x1a8dac800 | 0xa00000 | | 38 | blk.12.attn_norm.weight | 0x1a97ac800 | 0x5000 | | 39 | blk.12.ffn_down.weight | 0x1a97b1800 | 0x14000000 | | 40 | blk.12.ffn_gate.weight | 0x1bd7b1800 | 0x14000000 | | 41 | blk.12.ffn_up.weight | 0x1d17b1800 | 0x14000000 | | 42 | blk.12.ffn_norm.weight | 0x1e57b1800 | 0x5000 | | 43 | blk.12.attn_k.weight | 0x1e57b6800 | 0xa00000 | | 44 | blk.12.attn_output.weight | 0x1e61b6800 | 0x2800000 | | 45 | blk.12.attn_q.weight | 0x1e89b6800 | 0x2800000 | | 46 | blk.12.attn_v.weight | 0x1eb1b6800 | 0xa00000 | | 47 | blk.13.attn_norm.weight | 0x1ebbb6800 | 0x5000 | | 48 | blk.13.ffn_down.weight | 0x1ebbbb800 | 0x14000000 | | 49 | blk.13.ffn_gate.weight | 0x1ffbbb800 | 0x14000000 | | 50 | blk.13.ffn_up.weight | 0x213bbb800 | 0x14000000 | | 51 | blk.13.ffn_norm.weight | 0x227bbb800 | 0x5000 | | 52 | blk.13.attn_k.weight | 0x227bc0800 | 0xa00000 | | 53 | blk.13.attn_output.weight | 0x2285c0800 | 0x2800000 | | 54 | blk.13.attn_q.weight | 0x22adc0800 | 0x2800000 | | 55 | blk.13.attn_v.weight | 0x22d5c0800 | 0xa00000 | | 56 | blk.14.attn_norm.weight | 0x22dfc0800 | 0x5000 | | 57 | blk.14.ffn_down.weight | 0x22dfc5800 | 0x14000000 | | 58 | blk.14.ffn_gate.weight | 0x241fc5800 | 0x14000000 | | 59 | blk.14.ffn_up.weight | 0x255fc5800 | 0x14000000 | | 60 | blk.14.ffn_norm.weight | 0x269fc5800 | 0x5000 | | 61 | blk.14.attn_k.weight | 0x269fca800 | 0xa00000 | | 62 | blk.14.attn_output.weight | 0x26a9ca800 | 0x2800000 | | 63 | blk.14.attn_q.weight | 0x26d1ca800 | 0x2800000 | | 64 | blk.14.attn_v.weight | 0x26f9ca800 | 0xa00000 | | 65 | blk.15.attn_norm.weight | 0x2703ca800 | 0x5000 | | 66 | blk.15.ffn_down.weight | 0x2703cf800 | 0x14000000 | | 67 | blk.15.ffn_gate.weight | 0x2843cf800 | 0x14000000 | | 68 | blk.15.ffn_up.weight | 0x2983cf800 | 0x14000000 | | 69 | blk.15.ffn_norm.weight | 0x2ac3cf800 | 0x5000 | | 70 | blk.15.attn_k.weight | 0x2ac3d4800 | 0xa00000 | | 71 | blk.15.attn_output.weight | 0x2acdd4800 | 0x2800000 | | 72 | blk.15.attn_q.weight | 0x2af5d4800 | 0x2800000 | | 73 | blk.15.attn_v.weight | 0x2b1dd4800 | 0xa00000 | | 74 | blk.16.attn_norm.weight | 0x2b27d4800 | 0x5000 | | 75 | blk.16.ffn_down.weight | 0x2b27d9800 | 0x14000000 | | 76 | blk.16.ffn_gate.weight | 0x2c67d9800 | 0x14000000 | | 77 | blk.16.ffn_up.weight | 0x2da7d9800 | 0x14000000 | | 78 | blk.16.ffn_norm.weight | 0x2ee7d9800 | 0x5000 | | 79 | blk.16.attn_k.weight | 0x2ee7de800 | 0xa00000 | | 80 | blk.16.attn_output.weight | 0x2ef1de800 | 0x2800000 | | 81 | blk.16.attn_q.weight | 0x2f19de800 | 0x2800000 | | 82 | blk.16.attn_v.weight | 0x2f41de800 | 0xa00000 | | 83 | blk.17.attn_norm.weight | 0x2f4bde800 | 0x5000 | | 84 | blk.17.ffn_down.weight | 0x2f4be3800 | 0x14000000 | | 85 | blk.17.ffn_gate.weight | 0x308be3800 | 0x14000000 | | 86 | blk.17.ffn_up.weight | 0x31cbe3800 | 0x14000000 | | 87 | blk.17.ffn_norm.weight | 0x330be3800 | 0x5000 | | 88 | blk.17.attn_k.weight | 0x330be8800 | 0xa00000 | | 89 | blk.17.attn_output.weight | 0x3315e8800 | 0x2800000 | | 90 | blk.17.attn_q.weight | 0x333de8800 | 0x2800000 | | 91 | blk.17.attn_v.weight | 0x3365e8800 | 0xa00000 | | 92 | blk.18.attn_norm.weight | 0x336fe8800 | 0x5000 | | 93 | blk.18.ffn_down.weight | 0x336fed800 | 0x14000000 | | 94 | blk.18.ffn_gate.weight | 0x34afed800 | 0x14000000 | | 95 | blk.18.ffn_up.weight | 0x35efed800 | 0x14000000 | | 96 | blk.18.ffn_norm.weight | 0x372fed800 | 0x5000 | | 97 | blk.18.attn_k.weight | 0x372ff2800 | 0xa00000 | | 98 | blk.18.attn_output.weight | 0x3739f2800 | 0x2800000 | | 99 | blk.18.attn_q.weight | 0x3761f2800 | 0x2800000 | | 100 | blk.18.attn_v.weight | 0x3789f2800 | 0xa00000 | | 101 | blk.19.attn_norm.weight | 0x3793f2800 | 0x5000 | | 102 | blk.19.ffn_down.weight | 0x3793f7800 | 0x14000000 | | 103 | blk.19.ffn_gate.weight | 0x38d3f7800 | 0x14000000 | | 104 | blk.19.ffn_up.weight | 0x3a13f7800 | 0x14000000 | | 105 | blk.19.ffn_norm.weight | 0x3b53f7800 | 0x5000 | | 106 | blk.19.attn_k.weight | 0x3b53fc800 | 0xa00000 | | 107 | blk.19.attn_output.weight | 0x3b5dfc800 | 0x2800000 | | 108 | blk.19.attn_q.weight | 0x3b85fc800 | 0x2800000 | | 109 | blk.19.attn_v.weight | 0x3badfc800 | 0xa00000 | | 110 | blk.2.attn_norm.weight | 0x3bb7fc800 | 0x5000 | | 111 | blk.2.ffn_down.weight | 0x3bb801800 | 0x14000000 | | 112 | blk.2.ffn_gate.weight | 0x3cf801800 | 0x14000000 | | 113 | blk.2.ffn_up.weight | 0x3e3801800 | 0x14000000 | | 114 | blk.2.ffn_norm.weight | 0x3f7801800 | 0x5000 | | 115 | blk.2.attn_k.weight | 0x3f7806800 | 0xa00000 | | 116 | blk.2.attn_output.weight | 0x3f8206800 | 0x2800000 | | 117 | blk.2.attn_q.weight | 0x3faa06800 | 0x2800000 | | 118 | blk.2.attn_v.weight | 0x3fd206800 | 0xa00000 | | 119 | blk.20.attn_norm.weight | 0x3fdc06800 | 0x5000 | | 120 | blk.20.ffn_down.weight | 0x3fdc0b800 | 0x14000000 | | 121 | blk.20.ffn_gate.weight | 0x411c0b800 | 0x14000000 | | 122 | blk.20.ffn_up.weight | 0x425c0b800 | 0x14000000 | | 123 | blk.20.ffn_norm.weight | 0x439c0b800 | 0x5000 | | 124 | blk.20.attn_k.weight | 0x439c10800 | 0xa00000 | | 125 | blk.20.attn_output.weight | 0x43a610800 | 0x2800000 | | 126 | blk.20.attn_q.weight | 0x43ce10800 | 0x2800000 | | 127 | blk.20.attn_v.weight | 0x43f610800 | 0xa00000 | | 128 | blk.21.attn_norm.weight | 0x440010800 | 0x5000 | | 129 | blk.21.ffn_down.weight | 0x440015800 | 0x14000000 | | 130 | blk.21.ffn_gate.weight | 0x454015800 | 0x14000000 | | 131 | blk.21.ffn_up.weight | 0x468015800 | 0x14000000 | | 132 | blk.21.ffn_norm.weight | 0x47c015800 | 0x5000 | | 133 | blk.21.attn_k.weight | 0x47c01a800 | 0xa00000 | | 134 | blk.21.attn_output.weight | 0x47ca1a800 | 0x2800000 | | 135 | blk.21.attn_q.weight | 0x47f21a800 | 0x2800000 | | 136 | blk.21.attn_v.weight | 0x481a1a800 | 0xa00000 | | 137 | blk.22.attn_norm.weight | 0x48241a800 | 0x5000 | | 138 | blk.22.ffn_down.weight | 0x48241f800 | 0x14000000 | | 139 | blk.22.ffn_gate.weight | 0x49641f800 | 0x14000000 | | 140 | blk.22.ffn_up.weight | 0x4aa41f800 | 0x14000000 | | 141 | blk.22.ffn_norm.weight | 0x4be41f800 | 0x5000 | | 142 | blk.22.attn_k.weight | 0x4be424800 | 0xa00000 | | 143 | blk.22.attn_output.weight | 0x4bee24800 | 0x2800000 | | 144 | blk.22.attn_q.weight | 0x4c1624800 | 0x2800000 | | 145 | blk.22.attn_v.weight | 0x4c3e24800 | 0xa00000 | | 146 | blk.23.attn_norm.weight | 0x4c4824800 | 0x5000 | | 147 | blk.23.ffn_down.weight | 0x4c4829800 | 0x14000000 | | 148 | blk.23.ffn_gate.weight | 0x4d8829800 | 0x14000000 | | 149 | blk.23.ffn_up.weight | 0x4ec829800 | 0x14000000 | | 150 | blk.23.ffn_norm.weight | 0x500829800 | 0x5000 | | 151 | blk.23.attn_k.weight | 0x50082e800 | 0xa00000 | | 152 | blk.23.attn_output.weight | 0x50122e800 | 0x2800000 | | 153 | blk.23.attn_q.weight | 0x503a2e800 | 0x2800000 | | 154 | blk.23.attn_v.weight | 0x50622e800 | 0xa00000 | | 155 | blk.24.attn_norm.weight | 0x506c2e800 | 0x5000 | | 156 | blk.24.ffn_down.weight | 0x506c33800 | 0x14000000 | | 157 | blk.24.ffn_gate.weight | 0x51ac33800 | 0x14000000 | | 158 | blk.24.ffn_up.weight | 0x52ec33800 | 0x14000000 | | 159 | blk.24.ffn_norm.weight | 0x542c33800 | 0x5000 | | 160 | blk.24.attn_k.weight | 0x542c38800 | 0xa00000 | | 161 | blk.24.attn_output.weight | 0x543638800 | 0x2800000 | | 162 | blk.24.attn_q.weight | 0x545e38800 | 0x2800000 | | 163 | blk.24.attn_v.weight | 0x548638800 | 0xa00000 | | 164 | blk.25.attn_norm.weight | 0x549038800 | 0x5000 | | 165 | blk.25.ffn_down.weight | 0x54903d800 | 0x14000000 | | 166 | blk.25.ffn_gate.weight | 0x55d03d800 | 0x14000000 | | 167 | blk.25.ffn_up.weight | 0x57103d800 | 0x14000000 | | 168 | blk.25.ffn_norm.weight | 0x58503d800 | 0x5000 | | 169 | blk.25.attn_k.weight | 0x585042800 | 0xa00000 | | 170 | blk.25.attn_output.weight | 0x585a42800 | 0x2800000 | | 171 | blk.25.attn_q.weight | 0x588242800 | 0x2800000 | | 172 | blk.25.attn_v.weight | 0x58aa42800 | 0xa00000 | | 173 | blk.26.attn_norm.weight | 0x58b442800 | 0x5000 | | 174 | blk.26.ffn_down.weight | 0x58b447800 | 0x14000000 | | 175 | blk.26.ffn_gate.weight | 0x59f447800 | 0x14000000 | | 176 | blk.26.ffn_up.weight | 0x5b3447800 | 0x14000000 | | 177 | blk.26.ffn_norm.weight | 0x5c7447800 | 0x5000 | | 178 | blk.26.attn_k.weight | 0x5c744c800 | 0xa00000 | | 179 | blk.26.attn_output.weight | 0x5c7e4c800 | 0x2800000 | | 180 | blk.26.attn_q.weight | 0x5ca64c800 | 0x2800000 | | 181 | blk.26.attn_v.weight | 0x5cce4c800 | 0xa00000 | | 182 | blk.27.attn_norm.weight | 0x5cd84c800 | 0x5000 | | 183 | blk.27.ffn_down.weight | 0x5cd851800 | 0x14000000 | | 184 | blk.27.ffn_gate.weight | 0x5e1851800 | 0x14000000 | | 185 | blk.27.ffn_up.weight | 0x5f5851800 | 0x14000000 | | 186 | blk.27.ffn_norm.weight | 0x609851800 | 0x5000 | | 187 | blk.27.attn_k.weight | 0x609856800 | 0xa00000 | | 188 | blk.27.attn_output.weight | 0x60a256800 | 0x2800000 | | 189 | blk.27.attn_q.weight | 0x60ca56800 | 0x2800000 | | 190 | blk.27.attn_v.weight | 0x60f256800 | 0xa00000 | | 191 | blk.28.attn_norm.weight | 0x60fc56800 | 0x5000 | | 192 | blk.28.ffn_down.weight | 0x60fc5b800 | 0x14000000 | | 193 | blk.28.ffn_gate.weight | 0x623c5b800 | 0x14000000 | | 194 | blk.28.ffn_up.weight | 0x637c5b800 | 0x14000000 | | 195 | blk.28.ffn_norm.weight | 0x64bc5b800 | 0x5000 | | 196 | blk.28.attn_k.weight | 0x64bc60800 | 0xa00000 | | 197 | blk.28.attn_output.weight | 0x64c660800 | 0x2800000 | | 198 | blk.28.attn_q.weight | 0x64ee60800 | 0x2800000 | | 199 | blk.28.attn_v.weight | 0x651660800 | 0xa00000 | | 200 | blk.29.attn_norm.weight | 0x652060800 | 0x5000 | | 201 | blk.29.ffn_down.weight | 0x652065800 | 0x14000000 | | 202 | blk.29.ffn_gate.weight | 0x666065800 | 0x14000000 | | 203 | blk.29.ffn_up.weight | 0x67a065800 | 0x14000000 | | 204 | blk.29.ffn_norm.weight | 0x68e065800 | 0x5000 | | 205 | blk.29.attn_k.weight | 0x68e06a800 | 0xa00000 | | 206 | blk.29.attn_output.weight | 0x68ea6a800 | 0x2800000 | | 207 | blk.29.attn_q.weight | 0x69126a800 | 0x2800000 | | 208 | blk.29.attn_v.weight | 0x693a6a800 | 0xa00000 | | 209 | blk.3.attn_norm.weight | 0x69446a800 | 0x5000 | | 210 | blk.3.ffn_down.weight | 0x69446f800 | 0x14000000 | | 211 | blk.3.ffn_gate.weight | 0x6a846f800 | 0x14000000 | | 212 | blk.3.ffn_up.weight | 0x6bc46f800 | 0x14000000 | | 213 | blk.3.ffn_norm.weight | 0x6d046f800 | 0x5000 | | 214 | blk.3.attn_k.weight | 0x6d0474800 | 0xa00000 | | 215 | blk.3.attn_output.weight | 0x6d0e74800 | 0x2800000 | | 216 | blk.3.attn_q.weight | 0x6d3674800 | 0x2800000 | | 217 | blk.3.attn_v.weight | 0x6d5e74800 | 0xa00000 | | 218 | blk.30.attn_norm.weight | 0x6d6874800 | 0x5000 | | 219 | blk.30.ffn_down.weight | 0x6d6879800 | 0x14000000 | | 220 | blk.30.ffn_gate.weight | 0x6ea879800 | 0x14000000 | | 221 | blk.30.ffn_up.weight | 0x6fe879800 | 0x14000000 | | 222 | blk.30.ffn_norm.weight | 0x712879800 | 0x5000 | | 223 | blk.30.attn_k.weight | 0x71287e800 | 0xa00000 | | 224 | blk.30.attn_output.weight | 0x71327e800 | 0x2800000 | | 225 | blk.30.attn_q.weight | 0x715a7e800 | 0x2800000 | | 226 | blk.30.attn_v.weight | 0x71827e800 | 0xa00000 | | 227 | blk.31.attn_norm.weight | 0x718c7e800 | 0x5000 | | 228 | blk.31.ffn_down.weight | 0x718c83800 | 0x14000000 | | 229 | blk.31.ffn_gate.weight | 0x72cc83800 | 0x14000000 | | 230 | blk.31.ffn_up.weight | 0x740c83800 | 0x14000000 | | 231 | blk.31.ffn_norm.weight | 0x754c83800 | 0x5000 | | 232 | blk.31.attn_k.weight | 0x754c88800 | 0xa00000 | | 233 | blk.31.attn_output.weight | 0x755688800 | 0x2800000 | | 234 | blk.31.attn_q.weight | 0x757e88800 | 0x2800000 | | 235 | blk.31.attn_v.weight | 0x75a688800 | 0xa00000 | | 236 | blk.32.attn_norm.weight | 0x75b088800 | 0x5000 | | 237 | blk.32.ffn_down.weight | 0x75b08d800 | 0x14000000 | | 238 | blk.32.ffn_gate.weight | 0x76f08d800 | 0x14000000 | | 239 | blk.32.ffn_up.weight | 0x78308d800 | 0x14000000 | | 240 | blk.32.ffn_norm.weight | 0x79708d800 | 0x5000 | | 241 | blk.32.attn_k.weight | 0x797092800 | 0xa00000 | | 242 | blk.32.attn_output.weight | 0x797a92800 | 0x2800000 | | 243 | blk.32.attn_q.weight | 0x79a292800 | 0x2800000 | | 244 | blk.32.attn_v.weight | 0x79ca92800 | 0xa00000 | | 245 | blk.33.attn_norm.weight | 0x79d492800 | 0x5000 | | 246 | blk.33.ffn_down.weight | 0x79d497800 | 0x14000000 | | 247 | blk.33.ffn_gate.weight | 0x7b1497800 | 0x14000000 | | 248 | blk.33.ffn_up.weight | 0x7c5497800 | 0x14000000 | | 249 | blk.33.ffn_norm.weight | 0x7d9497800 | 0x5000 | | 250 | blk.33.attn_k.weight | 0x7d949c800 | 0xa00000 | | 251 | blk.33.attn_output.weight | 0x7d9e9c800 | 0x2800000 | | 252 | blk.33.attn_q.weight | 0x7dc69c800 | 0x2800000 | | 253 | blk.33.attn_v.weight | 0x7dee9c800 | 0xa00000 | | 254 | blk.34.attn_norm.weight | 0x7df89c800 | 0x5000 | | 255 | blk.34.ffn_down.weight | 0x7df8a1800 | 0x14000000 | | 256 | blk.34.ffn_gate.weight | 0x7f38a1800 | 0x14000000 | | 257 | blk.34.ffn_up.weight | 0x8078a1800 | 0x14000000 | | 258 | blk.34.ffn_norm.weight | 0x81b8a1800 | 0x5000 | | 259 | blk.34.attn_k.weight | 0x81b8a6800 | 0xa00000 | | 260 | blk.34.attn_output.weight | 0x81c2a6800 | 0x2800000 | | 261 | blk.34.attn_q.weight | 0x81eaa6800 | 0x2800000 | | 262 | blk.34.attn_v.weight | 0x8212a6800 | 0xa00000 | | 263 | blk.35.attn_norm.weight | 0x821ca6800 | 0x5000 | | 264 | blk.35.ffn_down.weight | 0x821cab800 | 0x14000000 | | 265 | blk.35.ffn_gate.weight | 0x835cab800 | 0x14000000 | | 266 | blk.35.ffn_up.weight | 0x849cab800 | 0x14000000 | | 267 | blk.35.ffn_norm.weight | 0x85dcab800 | 0x5000 | | 268 | blk.35.attn_k.weight | 0x85dcb0800 | 0xa00000 | | 269 | blk.35.attn_output.weight | 0x85e6b0800 | 0x2800000 | | 270 | blk.35.attn_q.weight | 0x860eb0800 | 0x2800000 | | 271 | blk.35.attn_v.weight | 0x8636b0800 | 0xa00000 | | 272 | blk.36.attn_norm.weight | 0x8640b0800 | 0x5000 | | 273 | blk.36.ffn_down.weight | 0x8640b5800 | 0x14000000 | | 274 | blk.36.ffn_gate.weight | 0x8780b5800 | 0x14000000 | | 275 | blk.36.ffn_up.weight | 0x88c0b5800 | 0x14000000 | | 276 | blk.36.ffn_norm.weight | 0x8a00b5800 | 0x5000 | | 277 | blk.36.attn_k.weight | 0x8a00ba800 | 0xa00000 | | 278 | blk.36.attn_output.weight | 0x8a0aba800 | 0x2800000 | | 279 | blk.36.attn_q.weight | 0x8a32ba800 | 0x2800000 | | 280 | blk.36.attn_v.weight | 0x8a5aba800 | 0xa00000 | | 281 | blk.37.attn_norm.weight | 0x8a64ba800 | 0x5000 | | 282 | blk.37.ffn_down.weight | 0x8a64bf800 | 0x14000000 | | 283 | blk.37.ffn_gate.weight | 0x8ba4bf800 | 0x14000000 | | 284 | blk.37.ffn_up.weight | 0x8ce4bf800 | 0x14000000 | | 285 | blk.37.ffn_norm.weight | 0x8e24bf800 | 0x5000 | | 286 | blk.37.attn_k.weight | 0x8e24c4800 | 0xa00000 | | 287 | blk.37.attn_output.weight | 0x8e2ec4800 | 0x2800000 | | 288 | blk.37.attn_q.weight | 0x8e56c4800 | 0x2800000 | | 289 | blk.37.attn_v.weight | 0x8e7ec4800 | 0xa00000 | | 290 | blk.38.attn_norm.weight | 0x8e88c4800 | 0x5000 | | 291 | blk.38.ffn_down.weight | 0x8e88c9800 | 0x14000000 | | 292 | blk.38.ffn_gate.weight | 0x8fc8c9800 | 0x14000000 | | 293 | blk.38.ffn_up.weight | 0x9108c9800 | 0x14000000 | | 294 | blk.38.ffn_norm.weight | 0x9248c9800 | 0x5000 | | 295 | blk.38.attn_k.weight | 0x9248ce800 | 0xa00000 | | 296 | blk.38.attn_output.weight | 0x9252ce800 | 0x2800000 | | 297 | blk.38.attn_q.weight | 0x927ace800 | 0x2800000 | | 298 | blk.38.attn_v.weight | 0x92a2ce800 | 0xa00000 | | 299 | blk.39.attn_norm.weight | 0x92acce800 | 0x5000 | | 300 | blk.39.ffn_down.weight | 0x92acd3800 | 0x14000000 | | 301 | blk.39.ffn_gate.weight | 0x93ecd3800 | 0x14000000 | | 302 | blk.39.ffn_up.weight | 0x952cd3800 | 0x14000000 | | 303 | blk.39.ffn_norm.weight | 0x966cd3800 | 0x5000 | | 304 | blk.39.attn_k.weight | 0x966cd8800 | 0xa00000 | | 305 | blk.39.attn_output.weight | 0x9676d8800 | 0x2800000 | | 306 | blk.39.attn_q.weight | 0x969ed8800 | 0x2800000 | | 307 | blk.39.attn_v.weight | 0x96c6d8800 | 0xa00000 | | 308 | blk.4.attn_norm.weight | 0x96d0d8800 | 0x5000 | | 309 | blk.4.ffn_down.weight | 0x96d0dd800 | 0x14000000 | | 310 | blk.4.ffn_gate.weight | 0x9810dd800 | 0x14000000 | | 311 | blk.4.ffn_up.weight | 0x9950dd800 | 0x14000000 | | 312 | blk.4.ffn_norm.weight | 0x9a90dd800 | 0x5000 | | 313 | blk.4.attn_k.weight | 0x9a90e2800 | 0xa00000 | | 314 | blk.4.attn_output.weight | 0x9a9ae2800 | 0x2800000 | | 315 | blk.4.attn_q.weight | 0x9ac2e2800 | 0x2800000 | | 316 | blk.4.attn_v.weight | 0x9aeae2800 | 0xa00000 | | 317 | blk.5.attn_norm.weight | 0x9af4e2800 | 0x5000 | | 318 | blk.5.ffn_down.weight | 0x9af4e7800 | 0x14000000 | | 319 | blk.5.ffn_gate.weight | 0x9c34e7800 | 0x14000000 | | 320 | blk.5.ffn_up.weight | 0x9d74e7800 | 0x14000000 | | 321 | blk.5.ffn_norm.weight | 0x9eb4e7800 | 0x5000 | | 322 | blk.5.attn_k.weight | 0x9eb4ec800 | 0xa00000 | | 323 | blk.5.attn_output.weight | 0x9ebeec800 | 0x2800000 | | 324 | blk.5.attn_q.weight | 0x9ee6ec800 | 0x2800000 | | 325 | blk.5.attn_v.weight | 0x9f0eec800 | 0xa00000 | | 326 | blk.6.attn_norm.weight | 0x9f18ec800 | 0x5000 | | 327 | blk.6.ffn_down.weight | 0x9f18f1800 | 0x14000000 | | 328 | blk.6.ffn_gate.weight | 0xa058f1800 | 0x14000000 | | 329 | blk.6.ffn_up.weight | 0xa198f1800 | 0x14000000 | | 330 | blk.6.ffn_norm.weight | 0xa2d8f1800 | 0x5000 | | 331 | blk.6.attn_k.weight | 0xa2d8f6800 | 0xa00000 | | 332 | blk.6.attn_output.weight | 0xa2e2f6800 | 0x2800000 | | 333 | blk.6.attn_q.weight | 0xa30af6800 | 0x2800000 | | 334 | blk.6.attn_v.weight | 0xa332f6800 | 0xa00000 | | 335 | blk.7.attn_norm.weight | 0xa33cf6800 | 0x5000 | | 336 | blk.7.ffn_down.weight | 0xa33cfb800 | 0x14000000 | | 337 | blk.7.ffn_gate.weight | 0xa47cfb800 | 0x14000000 | | 338 | blk.7.ffn_up.weight | 0xa5bcfb800 | 0x14000000 | | 339 | blk.7.ffn_norm.weight | 0xa6fcfb800 | 0x5000 | | 340 | blk.7.attn_k.weight | 0xa6fd00800 | 0xa00000 | | 341 | blk.7.attn_output.weight | 0xa70700800 | 0x2800000 | | 342 | blk.7.attn_q.weight | 0xa72f00800 | 0x2800000 | | 343 | blk.7.attn_v.weight | 0xa75700800 | 0xa00000 | | 344 | blk.8.attn_norm.weight | 0xa76100800 | 0x5000 | | 345 | blk.8.ffn_down.weight | 0xa76105800 | 0x14000000 | | 346 | blk.8.ffn_gate.weight | 0xa8a105800 | 0x14000000 | | 347 | blk.8.ffn_up.weight | 0xa9e105800 | 0x14000000 | | 348 | blk.8.ffn_norm.weight | 0xab2105800 | 0x5000 | | 349 | blk.8.attn_k.weight | 0xab210a800 | 0xa00000 | | 350 | blk.8.attn_output.weight | 0xab2b0a800 | 0x2800000 | | 351 | blk.8.attn_q.weight | 0xab530a800 | 0x2800000 | | 352 | blk.8.attn_v.weight | 0xab7b0a800 | 0xa00000 | | 353 | blk.9.attn_norm.weight | 0xab850a800 | 0x5000 | | 354 | blk.9.ffn_down.weight | 0xab850f800 | 0x14000000 | | 355 | blk.9.ffn_gate.weight | 0xacc50f800 | 0x14000000 | | 356 | blk.9.ffn_up.weight | 0xae050f800 | 0x14000000 | | 357 | blk.9.ffn_norm.weight | 0xaf450f800 | 0x5000 | | 358 | blk.9.attn_k.weight | 0xaf4514800 | 0xa00000 | | 359 | blk.9.attn_output.weight | 0xaf4f14800 | 0x2800000 | | 360 | blk.9.attn_q.weight | 0xaf7714800 | 0x2800000 | | 361 | blk.9.attn_v.weight | 0xaf9f14800 | 0xa00000 | | 362 | output_norm.weight | 0xafa914800 | 0x5000 | ### Base Tensor Group : ~1B Elements | 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 | F16 | | 1 | token_embd.weight | Token Embedding (W) | (~671M) 671088640 | 5120 x 131072 x 1 x 1 | F16 | | 362 | output_norm.weight | Output Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | - Total elements in base: ( ~1B) 1342182400 - Percentage of total elements: 5.69% ### Block 0 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----| | 2 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 3 | blk.0.ffn_down.weight | Block 0 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 4 | blk.0.ffn_gate.weight | Block 0 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 5 | blk.0.ffn_up.weight | Block 0 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 6 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 7 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 8 | blk.0.attn_output.weight | Block 0 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 9 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 10 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.0: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 1 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----| | 11 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 12 | blk.1.ffn_down.weight | Block 1 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 13 | blk.1.ffn_gate.weight | Block 1 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 14 | blk.1.ffn_up.weight | Block 1 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 15 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 16 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 17 | blk.1.attn_output.weight | Block 1 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 18 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 19 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.1: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 10 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 20 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 21 | blk.10.ffn_down.weight | Block 10 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 22 | blk.10.ffn_gate.weight | Block 10 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 23 | blk.10.ffn_up.weight | Block 10 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 24 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 25 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 26 | blk.10.attn_output.weight | Block 10 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 27 | blk.10.attn_q.weight | Block 10 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 28 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.10: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 11 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 29 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 30 | blk.11.ffn_down.weight | Block 11 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 31 | blk.11.ffn_gate.weight | Block 11 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 32 | blk.11.ffn_up.weight | Block 11 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 33 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 34 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 35 | blk.11.attn_output.weight | Block 11 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 36 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 37 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.11: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 12 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 38 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 39 | blk.12.ffn_down.weight | Block 12 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 40 | blk.12.ffn_gate.weight | Block 12 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 41 | blk.12.ffn_up.weight | Block 12 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 42 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 43 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 44 | blk.12.attn_output.weight | Block 12 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 45 | blk.12.attn_q.weight | Block 12 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 46 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.12: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 13 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 47 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 48 | blk.13.ffn_down.weight | Block 13 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 49 | blk.13.ffn_gate.weight | Block 13 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 50 | blk.13.ffn_up.weight | Block 13 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 51 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 52 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 53 | blk.13.attn_output.weight | Block 13 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 54 | blk.13.attn_q.weight | Block 13 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 55 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.13: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 14 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 56 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 57 | blk.14.ffn_down.weight | Block 14 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 58 | blk.14.ffn_gate.weight | Block 14 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 59 | blk.14.ffn_up.weight | Block 14 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 60 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 61 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 62 | blk.14.attn_output.weight | Block 14 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 63 | blk.14.attn_q.weight | Block 14 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 64 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.14: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 15 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 65 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 66 | blk.15.ffn_down.weight | Block 15 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 67 | blk.15.ffn_gate.weight | Block 15 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 68 | blk.15.ffn_up.weight | Block 15 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 69 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 70 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 71 | blk.15.attn_output.weight | Block 15 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 72 | blk.15.attn_q.weight | Block 15 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 73 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.15: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 16 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 74 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 75 | blk.16.ffn_down.weight | Block 16 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 76 | blk.16.ffn_gate.weight | Block 16 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 77 | blk.16.ffn_up.weight | Block 16 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 78 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 79 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 80 | blk.16.attn_output.weight | Block 16 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 81 | blk.16.attn_q.weight | Block 16 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 82 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.16: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 17 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 83 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 84 | blk.17.ffn_down.weight | Block 17 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 85 | blk.17.ffn_gate.weight | Block 17 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 86 | blk.17.ffn_up.weight | Block 17 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 87 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 88 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 89 | blk.17.attn_output.weight | Block 17 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 90 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 91 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.17: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 18 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 92 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 93 | blk.18.ffn_down.weight | Block 18 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 94 | blk.18.ffn_gate.weight | Block 18 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 95 | blk.18.ffn_up.weight | Block 18 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 96 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 97 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 98 | blk.18.attn_output.weight | Block 18 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 99 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 100 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.18: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 19 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 101 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 102 | blk.19.ffn_down.weight | Block 19 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 103 | blk.19.ffn_gate.weight | Block 19 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 104 | blk.19.ffn_up.weight | Block 19 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 105 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 106 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 107 | blk.19.attn_output.weight | Block 19 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 108 | blk.19.attn_q.weight | Block 19 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 109 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.19: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 2 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----| | 110 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 111 | blk.2.ffn_down.weight | Block 2 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 112 | blk.2.ffn_gate.weight | Block 2 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 113 | blk.2.ffn_up.weight | Block 2 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 114 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 115 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 116 | blk.2.attn_output.weight | Block 2 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 117 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 118 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.2: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 20 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 119 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 120 | blk.20.ffn_down.weight | Block 20 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 121 | blk.20.ffn_gate.weight | Block 20 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 122 | blk.20.ffn_up.weight | Block 20 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 123 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 124 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 125 | blk.20.attn_output.weight | Block 20 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 126 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 127 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.20: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 21 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 128 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 129 | blk.21.ffn_down.weight | Block 21 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 130 | blk.21.ffn_gate.weight | Block 21 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 131 | blk.21.ffn_up.weight | Block 21 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 132 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 133 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 134 | blk.21.attn_output.weight | Block 21 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 135 | blk.21.attn_q.weight | Block 21 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 136 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.21: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 22 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 137 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 138 | blk.22.ffn_down.weight | Block 22 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 139 | blk.22.ffn_gate.weight | Block 22 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 140 | blk.22.ffn_up.weight | Block 22 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 141 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 142 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 143 | blk.22.attn_output.weight | Block 22 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 144 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 145 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.22: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 23 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 146 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 147 | blk.23.ffn_down.weight | Block 23 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 148 | blk.23.ffn_gate.weight | Block 23 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 149 | blk.23.ffn_up.weight | Block 23 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 150 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 151 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 152 | blk.23.attn_output.weight | Block 23 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 153 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 154 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.23: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 24 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 155 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 156 | blk.24.ffn_down.weight | Block 24 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 157 | blk.24.ffn_gate.weight | Block 24 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 158 | blk.24.ffn_up.weight | Block 24 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 159 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 160 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 161 | blk.24.attn_output.weight | Block 24 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 162 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 163 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.24: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 25 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 164 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 165 | blk.25.ffn_down.weight | Block 25 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 166 | blk.25.ffn_gate.weight | Block 25 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 167 | blk.25.ffn_up.weight | Block 25 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 168 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 169 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 170 | blk.25.attn_output.weight | Block 25 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 171 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 172 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.25: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 26 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 173 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 174 | blk.26.ffn_down.weight | Block 26 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 175 | blk.26.ffn_gate.weight | Block 26 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 176 | blk.26.ffn_up.weight | Block 26 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 177 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 178 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 179 | blk.26.attn_output.weight | Block 26 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 180 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 181 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.26: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 27 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 182 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 183 | blk.27.ffn_down.weight | Block 27 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 184 | blk.27.ffn_gate.weight | Block 27 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 185 | blk.27.ffn_up.weight | Block 27 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 186 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 187 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 188 | blk.27.attn_output.weight | Block 27 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 189 | blk.27.attn_q.weight | Block 27 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 190 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.27: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 28 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 191 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 192 | blk.28.ffn_down.weight | Block 28 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 193 | blk.28.ffn_gate.weight | Block 28 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 194 | blk.28.ffn_up.weight | Block 28 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 195 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 196 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 197 | blk.28.attn_output.weight | Block 28 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 198 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 199 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.28: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 29 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 200 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 201 | blk.29.ffn_down.weight | Block 29 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 202 | blk.29.ffn_gate.weight | Block 29 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 203 | blk.29.ffn_up.weight | Block 29 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 204 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 205 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 206 | blk.29.attn_output.weight | Block 29 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 207 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 208 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.29: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 3 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----| | 209 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 210 | blk.3.ffn_down.weight | Block 3 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 211 | blk.3.ffn_gate.weight | Block 3 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 212 | blk.3.ffn_up.weight | Block 3 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 213 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 214 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 215 | blk.3.attn_output.weight | Block 3 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 216 | blk.3.attn_q.weight | Block 3 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 217 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.3: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 30 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 218 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 219 | blk.30.ffn_down.weight | Block 30 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 220 | blk.30.ffn_gate.weight | Block 30 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 221 | blk.30.ffn_up.weight | Block 30 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 222 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 223 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 224 | blk.30.attn_output.weight | Block 30 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 225 | blk.30.attn_q.weight | Block 30 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 226 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.30: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 31 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 227 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 228 | blk.31.ffn_down.weight | Block 31 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 229 | blk.31.ffn_gate.weight | Block 31 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 230 | blk.31.ffn_up.weight | Block 31 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 231 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 232 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 233 | blk.31.attn_output.weight | Block 31 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 234 | blk.31.attn_q.weight | Block 31 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 235 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.31: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 32 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 236 | blk.32.attn_norm.weight | Block 32 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 237 | blk.32.ffn_down.weight | Block 32 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 238 | blk.32.ffn_gate.weight | Block 32 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 239 | blk.32.ffn_up.weight | Block 32 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 240 | blk.32.ffn_norm.weight | Block 32 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 241 | blk.32.attn_k.weight | Block 32 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 242 | blk.32.attn_output.weight | Block 32 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 243 | blk.32.attn_q.weight | Block 32 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 244 | blk.32.attn_v.weight | Block 32 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.32: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 33 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 245 | blk.33.attn_norm.weight | Block 33 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 246 | blk.33.ffn_down.weight | Block 33 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 247 | blk.33.ffn_gate.weight | Block 33 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 248 | blk.33.ffn_up.weight | Block 33 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 249 | blk.33.ffn_norm.weight | Block 33 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 250 | blk.33.attn_k.weight | Block 33 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 251 | blk.33.attn_output.weight | Block 33 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 252 | blk.33.attn_q.weight | Block 33 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 253 | blk.33.attn_v.weight | Block 33 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.33: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 34 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 254 | blk.34.attn_norm.weight | Block 34 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 255 | blk.34.ffn_down.weight | Block 34 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 256 | blk.34.ffn_gate.weight | Block 34 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 257 | blk.34.ffn_up.weight | Block 34 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 258 | blk.34.ffn_norm.weight | Block 34 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 259 | blk.34.attn_k.weight | Block 34 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 260 | blk.34.attn_output.weight | Block 34 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 261 | blk.34.attn_q.weight | Block 34 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 262 | blk.34.attn_v.weight | Block 34 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.34: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 35 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 263 | blk.35.attn_norm.weight | Block 35 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 264 | blk.35.ffn_down.weight | Block 35 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 265 | blk.35.ffn_gate.weight | Block 35 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 266 | blk.35.ffn_up.weight | Block 35 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 267 | blk.35.ffn_norm.weight | Block 35 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 268 | blk.35.attn_k.weight | Block 35 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 269 | blk.35.attn_output.weight | Block 35 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 270 | blk.35.attn_q.weight | Block 35 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 271 | blk.35.attn_v.weight | Block 35 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.35: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 36 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 272 | blk.36.attn_norm.weight | Block 36 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 273 | blk.36.ffn_down.weight | Block 36 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 274 | blk.36.ffn_gate.weight | Block 36 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 275 | blk.36.ffn_up.weight | Block 36 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 276 | blk.36.ffn_norm.weight | Block 36 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 277 | blk.36.attn_k.weight | Block 36 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 278 | blk.36.attn_output.weight | Block 36 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 279 | blk.36.attn_q.weight | Block 36 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 280 | blk.36.attn_v.weight | Block 36 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.36: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 37 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 281 | blk.37.attn_norm.weight | Block 37 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 282 | blk.37.ffn_down.weight | Block 37 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 283 | blk.37.ffn_gate.weight | Block 37 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 284 | blk.37.ffn_up.weight | Block 37 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 285 | blk.37.ffn_norm.weight | Block 37 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 286 | blk.37.attn_k.weight | Block 37 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 287 | blk.37.attn_output.weight | Block 37 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 288 | blk.37.attn_q.weight | Block 37 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 289 | blk.37.attn_v.weight | Block 37 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.37: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 38 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 290 | blk.38.attn_norm.weight | Block 38 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 291 | blk.38.ffn_down.weight | Block 38 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 292 | blk.38.ffn_gate.weight | Block 38 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 293 | blk.38.ffn_up.weight | Block 38 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 294 | blk.38.ffn_norm.weight | Block 38 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 295 | blk.38.attn_k.weight | Block 38 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 296 | blk.38.attn_output.weight | Block 38 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 297 | blk.38.attn_q.weight | Block 38 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 298 | blk.38.attn_v.weight | Block 38 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.38: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 39 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:--------------------------|:------------------------------------------------|:------------------|:----------------------|:-----| | 299 | blk.39.attn_norm.weight | Block 39 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 300 | blk.39.ffn_down.weight | Block 39 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 301 | blk.39.ffn_gate.weight | Block 39 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 302 | blk.39.ffn_up.weight | Block 39 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 303 | blk.39.ffn_norm.weight | Block 39 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 304 | blk.39.attn_k.weight | Block 39 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 305 | blk.39.attn_output.weight | Block 39 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 306 | blk.39.attn_q.weight | Block 39 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 307 | blk.39.attn_v.weight | Block 39 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.39: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 4 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----| | 308 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 309 | blk.4.ffn_down.weight | Block 4 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 310 | blk.4.ffn_gate.weight | Block 4 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 311 | blk.4.ffn_up.weight | Block 4 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 312 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 313 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 314 | blk.4.attn_output.weight | Block 4 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 315 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 316 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.4: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 5 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----| | 317 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 318 | blk.5.ffn_down.weight | Block 5 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 319 | blk.5.ffn_gate.weight | Block 5 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 320 | blk.5.ffn_up.weight | Block 5 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 321 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 322 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 323 | blk.5.attn_output.weight | Block 5 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 324 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 325 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.5: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 6 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----| | 326 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 327 | blk.6.ffn_down.weight | Block 6 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 328 | blk.6.ffn_gate.weight | Block 6 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 329 | blk.6.ffn_up.weight | Block 6 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 330 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 331 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 332 | blk.6.attn_output.weight | Block 6 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 333 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 334 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.6: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 7 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----| | 335 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 336 | blk.7.ffn_down.weight | Block 7 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 337 | blk.7.ffn_gate.weight | Block 7 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 338 | blk.7.ffn_up.weight | Block 7 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 339 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 340 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 341 | blk.7.attn_output.weight | Block 7 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 342 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 343 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.7: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 8 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----| | 344 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 345 | blk.8.ffn_down.weight | Block 8 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 346 | blk.8.ffn_gate.weight | Block 8 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 347 | blk.8.ffn_up.weight | Block 8 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 348 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 349 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 350 | blk.8.attn_output.weight | Block 8 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 351 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 352 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.8: (~556M) 555755520 - Percentage of total elements: 2.36% ### Block 9 Tensor Group : ~556M Elements | T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type | |-----:|:-------------------------|:-----------------------------------------------|:------------------|:----------------------|:-----| | 353 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 354 | blk.9.ffn_down.weight | Block 9 Feed-Forward Network "Down" (W) | (~168M) 167772160 | 32768 x 5120 x 1 x 1 | F16 | | 355 | blk.9.ffn_gate.weight | Block 9 Feed-Forward Network "Gate" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 356 | blk.9.ffn_up.weight | Block 9 Feed-Forward Network "Up" (W) | (~168M) 167772160 | 5120 x 32768 x 1 x 1 | F16 | | 357 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~5K) 5120 | 5120 x 1 x 1 x 1 | F32 | | 358 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | | 359 | blk.9.attn_output.weight | Block 9 Attention Output (W) | ( ~21M) 20971520 | 4096 x 5120 x 1 x 1 | F16 | | 360 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~21M) 20971520 | 5120 x 4096 x 1 x 1 | F16 | | 361 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~5M) 5242880 | 5120 x 1024 x 1 x 1 | F16 | - Total elements in blk.9: (~556M) 555755520 - Percentage of total elements: 2.36%