diff --git "a/scores/Qwen3-30B-A3B-pruned-Q5_K_M.md" "b/scores/Qwen3-30B-A3B-pruned-Q5_K_M.md"
new file mode 100644--- /dev/null
+++ "b/scores/Qwen3-30B-A3B-pruned-Q5_K_M.md"
@@ -0,0 +1,1653 @@
+# Qwen3-30B-A3B-Q5_K_M.gguf - GGUF Internal File Dump
+
+- Endian: LITTLE endian
+
+## Key Value Metadata Store
+
+There are 45 key-value pairs in this file
+
+| POS | TYPE | Count | Key | Value |
+|----:|:---------|-------:|:------------------------------------------|:--------------------------------------------------------------------|
+| 1 | UINT32 | 1 | GGUF.version | 3 |
+| 2 | UINT64 | 1 | GGUF.tensor_count | 555 |
+| 3 | UINT64 | 1 | GGUF.kv_count | 42 |
+| 4 | STRING | 1 | general.architecture | `qwen3moe` |
+| 5 | STRING | 1 | general.type | `model` |
+| 6 | STRING | 1 | general.name | `Qwen3 30B A3B` |
+| 7 | STRING | 1 | general.basename | `Qwen3` |
+| 8 | STRING | 1 | general.size_label | `30B-A3B` |
+| 9 | STRING | 1 | general.license | `apache-2.0` |
+| 10 | STRING | 1 | general.license.link | `https://huggingface.co/Qwen/Qwen3-30B-A3B/blob/main/LICENSE` |
+| 11 | UINT32 | 1 | general.base_model.count | 1 |
+| 12 | STRING | 1 | general.base_model.0.name | `Qwen3 30B A3B Base` |
+| 13 | STRING | 1 | general.base_model.0.organization | `Qwen` |
+| 14 | STRING | 1 | general.base_model.0.repo_url | `https://huggingface.co/Qwen/Qwen3-30B-A3B-Base` |
+| 15 | [STRING] | 1 | general.tags | [ `text-generation` ] |
+| 16 | UINT32 | 1 | qwen3moe.context_length | 40960 |
+| 17 | UINT32 | 1 | qwen3moe.embedding_length | 2048 |
+| 18 | UINT32 | 1 | qwen3moe.feed_forward_length | 6144 |
+| 19 | UINT32 | 1 | qwen3moe.attention.head_count | 32 |
+| 20 | UINT32 | 1 | qwen3moe.attention.head_count_kv | 4 |
+| 21 | FLOAT32 | 1 | qwen3moe.rope.freq_base | 1000000.0 |
+| 22 | FLOAT32 | 1 | qwen3moe.attention.layer_norm_rms_epsilon | 1e-06 |
+| 23 | UINT32 | 1 | qwen3moe.expert_used_count | 8 |
+| 24 | UINT32 | 1 | qwen3moe.attention.key_length | 128 |
+| 25 | UINT32 | 1 | qwen3moe.attention.value_length | 128 |
+| 26 | UINT32 | 1 | qwen3moe.expert_count | 128 |
+| 27 | UINT32 | 1 | qwen3moe.expert_feed_forward_length | 768 |
+| 28 | STRING | 1 | tokenizer.ggml.model | `gpt2` |
+| 29 | STRING | 1 | tokenizer.ggml.pre | `qwen2` |
+| 30 | [STRING] | 151936 | tokenizer.ggml.tokens | [ `!`, `"`, `#`, `$`, `%`, ... ] |
+| 31 | [INT32] | 151936 | tokenizer.ggml.token_type | [ 1, 1, 1, 1, 1, 1, 1, ... ] |
+| 32 | [STRING] | 151387 | tokenizer.ggml.merges | [ `Ġ Ġ`, `ĠĠ ĠĠ`, `i n`, `Ġ t`, `ĠĠĠĠ ĠĠĠĠ`, ... ] |
+| 33 | UINT32 | 1 | tokenizer.ggml.eos_token_id | 151645 |
+| 34 | UINT32 | 1 | tokenizer.ggml.padding_token_id | 151643 |
+| 35 | UINT32 | 1 | tokenizer.ggml.bos_token_id | 151643 |
+| 36 | BOOL | 1 | tokenizer.ggml.add_bos_token | False |
+| 37 | STRING | 1 | tokenizer.chat_template | `{%- if tools %}{{- '<|im_`...`{%- endif %}{%- endif %}` |
+| 38 | UINT32 | 1 | general.quantization_version | 2 |
+| 39 | UINT32 | 1 | general.file_type | 17 |
+| 40 | BOOL | 1 | general.pruned | True |
+| 41 | UINT32 | 1 | qwen3moe.block_count | 46 |
+| 42 | STRING | 1 | quantize.imatrix.file | `./imatrix/imatrix-Qwen3-30B-A3B-medium.dat` |
+| 43 | STRING | 1 | quantize.imatrix.dataset | `../../datasets/imatrix/combined_all_medium.txt` |
+| 44 | INT32 | 1 | quantize.imatrix.entries_count | 385 |
+| 45 | INT32 | 1 | quantize.imatrix.chunks_count | 6946 |
+
+## Tensors Overview ~29B Elements
+
+Total number of elements in all tensors: 29285881344 Elements
+
+- [Qwen3-30B-A3B-Q5\_K\_M.gguf - GGUF Internal File Dump](#qwen3-30b-a3b-q5_k_mgguf---gguf-internal-file-dump)
+ - [Key Value Metadata Store](#key-value-metadata-store)
+ - [Tensors Overview ~29B Elements](#tensors-overview-29b-elements)
+ - [Tensor Data Offset](#tensor-data-offset)
+ - [Base Tensor Group : ~622M Elements](#base-tensor-group--622m-elements)
+ - [Block 0 Tensor Group : ~623M Elements](#block-0-tensor-group--623m-elements)
+ - [Block 1 Tensor Group : ~623M Elements](#block-1-tensor-group--623m-elements)
+ - [Block 2 Tensor Group : ~623M Elements](#block-2-tensor-group--623m-elements)
+ - [Block 3 Tensor Group : ~623M Elements](#block-3-tensor-group--623m-elements)
+ - [Block 4 Tensor Group : ~623M Elements](#block-4-tensor-group--623m-elements)
+ - [Block 5 Tensor Group : ~623M Elements](#block-5-tensor-group--623m-elements)
+ - [Block 6 Tensor Group : ~623M Elements](#block-6-tensor-group--623m-elements)
+ - [Block 7 Tensor Group : ~623M Elements](#block-7-tensor-group--623m-elements)
+ - [Block 8 Tensor Group : ~623M Elements](#block-8-tensor-group--623m-elements)
+ - [Block 9 Tensor Group : ~623M Elements](#block-9-tensor-group--623m-elements)
+ - [Block 10 Tensor Group : ~623M Elements](#block-10-tensor-group--623m-elements)
+ - [Block 11 Tensor Group : ~623M Elements](#block-11-tensor-group--623m-elements)
+ - [Block 12 Tensor Group : ~623M Elements](#block-12-tensor-group--623m-elements)
+ - [Block 13 Tensor Group : ~623M Elements](#block-13-tensor-group--623m-elements)
+ - [Block 14 Tensor Group : ~623M Elements](#block-14-tensor-group--623m-elements)
+ - [Block 15 Tensor Group : ~623M Elements](#block-15-tensor-group--623m-elements)
+ - [Block 16 Tensor Group : ~623M Elements](#block-16-tensor-group--623m-elements)
+ - [Block 17 Tensor Group : ~623M Elements](#block-17-tensor-group--623m-elements)
+ - [Block 18 Tensor Group : ~623M Elements](#block-18-tensor-group--623m-elements)
+ - [Block 19 Tensor Group : ~623M Elements](#block-19-tensor-group--623m-elements)
+ - [Block 20 Tensor Group : ~623M Elements](#block-20-tensor-group--623m-elements)
+ - [Block 21 Tensor Group : ~623M Elements](#block-21-tensor-group--623m-elements)
+ - [Block 22 Tensor Group : ~623M Elements](#block-22-tensor-group--623m-elements)
+ - [Block 23 Tensor Group : ~623M Elements](#block-23-tensor-group--623m-elements)
+ - [Block 24 Tensor Group : ~623M Elements](#block-24-tensor-group--623m-elements)
+ - [Block 25 Tensor Group : ~623M Elements](#block-25-tensor-group--623m-elements)
+ - [Block 26 Tensor Group : ~623M Elements](#block-26-tensor-group--623m-elements)
+ - [Block 27 Tensor Group : ~623M Elements](#block-27-tensor-group--623m-elements)
+ - [Block 28 Tensor Group : ~623M Elements](#block-28-tensor-group--623m-elements)
+ - [Block 29 Tensor Group : ~623M Elements](#block-29-tensor-group--623m-elements)
+ - [Block 30 Tensor Group : ~623M Elements](#block-30-tensor-group--623m-elements)
+ - [Block 31 Tensor Group : ~623M Elements](#block-31-tensor-group--623m-elements)
+ - [Block 32 Tensor Group : ~623M Elements](#block-32-tensor-group--623m-elements)
+ - [Block 33 Tensor Group : ~623M Elements](#block-33-tensor-group--623m-elements)
+ - [Block 34 Tensor Group : ~623M Elements](#block-34-tensor-group--623m-elements)
+ - [Block 35 Tensor Group : ~623M Elements](#block-35-tensor-group--623m-elements)
+ - [Block 36 Tensor Group : ~623M Elements](#block-36-tensor-group--623m-elements)
+ - [Block 37 Tensor Group : ~623M Elements](#block-37-tensor-group--623m-elements)
+ - [Block 38 Tensor Group : ~623M Elements](#block-38-tensor-group--623m-elements)
+ - [Block 39 Tensor Group : ~623M Elements](#block-39-tensor-group--623m-elements)
+ - [Block 40 Tensor Group : ~623M Elements](#block-40-tensor-group--623m-elements)
+ - [Block 41 Tensor Group : ~623M Elements](#block-41-tensor-group--623m-elements)
+ - [Block 42 Tensor Group : ~623M Elements](#block-42-tensor-group--623m-elements)
+ - [Block 43 Tensor Group : ~623M Elements](#block-43-tensor-group--623m-elements)
+ - [Block 44 Tensor Group : ~623M Elements](#block-44-tensor-group--623m-elements)
+ - [Block 45 Tensor Group : ~623M Elements](#block-45-tensor-group--623m-elements)
+
+### Tensor Data Offset
+
+This table contains the offset and data segment relative to start of file
+
+| T_ID | Tensor Layer Name | Data Offset (B) | Data Size (B) |
+|-----:|:----------------------------|-----------------:|-----------------:|
+| 0 | output.weight | 0x5b12e0 | 0xcc04000 |
+| 1 | output_norm.weight | 0xd1b52e0 | 0x2000 |
+| 2 | token_embd.weight | 0xd1b72e0 | 0x7f82800 |
+| 3 | blk.0.attn_k.weight | 0x15139ae0 | 0x90000 |
+| 4 | blk.0.attn_k_norm.weight | 0x151c9ae0 | 0x200 |
+| 5 | blk.0.attn_norm.weight | 0x151c9ce0 | 0x2000 |
+| 6 | blk.0.attn_output.weight | 0x151cbce0 | 0x580000 |
+| 7 | blk.0.attn_q.weight | 0x1574bce0 | 0x480000 |
+| 8 | blk.0.attn_q_norm.weight | 0x15bcbce0 | 0x200 |
+| 9 | blk.0.attn_v.weight | 0x15bcbee0 | 0xb0000 |
+| 10 | blk.0.ffn_down_exps.weight | 0x15c7bee0 | 0x9d80000 |
+| 11 | blk.0.ffn_gate_exps.weight | 0x1f9fbee0 | 0x6c00000 |
+| 12 | blk.0.ffn_gate_inp.weight | 0x265fbee0 | 0x100000 |
+| 13 | blk.0.ffn_norm.weight | 0x266fbee0 | 0x2000 |
+| 14 | blk.0.ffn_up_exps.weight | 0x266fdee0 | 0x6c00000 |
+| 15 | blk.1.attn_k.weight | 0x2d2fdee0 | 0x90000 |
+| 16 | blk.1.attn_k_norm.weight | 0x2d38dee0 | 0x200 |
+| 17 | blk.1.attn_norm.weight | 0x2d38e0e0 | 0x2000 |
+| 18 | blk.1.attn_output.weight | 0x2d3900e0 | 0x580000 |
+| 19 | blk.1.attn_q.weight | 0x2d9100e0 | 0x480000 |
+| 20 | blk.1.attn_q_norm.weight | 0x2dd900e0 | 0x200 |
+| 21 | blk.1.attn_v.weight | 0x2dd902e0 | 0xb0000 |
+| 22 | blk.1.ffn_down_exps.weight | 0x2de402e0 | 0x9d80000 |
+| 23 | blk.1.ffn_gate_exps.weight | 0x37bc02e0 | 0x6c00000 |
+| 24 | blk.1.ffn_gate_inp.weight | 0x3e7c02e0 | 0x100000 |
+| 25 | blk.1.ffn_norm.weight | 0x3e8c02e0 | 0x2000 |
+| 26 | blk.1.ffn_up_exps.weight | 0x3e8c22e0 | 0x6c00000 |
+| 27 | blk.2.attn_k.weight | 0x454c22e0 | 0x90000 |
+| 28 | blk.2.attn_k_norm.weight | 0x455522e0 | 0x200 |
+| 29 | blk.2.attn_norm.weight | 0x455524e0 | 0x2000 |
+| 30 | blk.2.attn_output.weight | 0x455544e0 | 0x580000 |
+| 31 | blk.2.attn_q.weight | 0x45ad44e0 | 0x480000 |
+| 32 | blk.2.attn_q_norm.weight | 0x45f544e0 | 0x200 |
+| 33 | blk.2.attn_v.weight | 0x45f546e0 | 0xb0000 |
+| 34 | blk.2.ffn_down_exps.weight | 0x460046e0 | 0x9d80000 |
+| 35 | blk.2.ffn_gate_exps.weight | 0x4fd846e0 | 0x6c00000 |
+| 36 | blk.2.ffn_gate_inp.weight | 0x569846e0 | 0x100000 |
+| 37 | blk.2.ffn_norm.weight | 0x56a846e0 | 0x2000 |
+| 38 | blk.2.ffn_up_exps.weight | 0x56a866e0 | 0x6c00000 |
+| 39 | blk.3.attn_k.weight | 0x5d6866e0 | 0x90000 |
+| 40 | blk.3.attn_k_norm.weight | 0x5d7166e0 | 0x200 |
+| 41 | blk.3.attn_norm.weight | 0x5d7168e0 | 0x2000 |
+| 42 | blk.3.attn_output.weight | 0x5d7188e0 | 0x580000 |
+| 43 | blk.3.attn_q.weight | 0x5dc988e0 | 0x480000 |
+| 44 | blk.3.attn_q_norm.weight | 0x5e1188e0 | 0x200 |
+| 45 | blk.3.attn_v.weight | 0x5e118ae0 | 0xb0000 |
+| 46 | blk.3.ffn_down_exps.weight | 0x5e1c8ae0 | 0x9d80000 |
+| 47 | blk.3.ffn_gate_exps.weight | 0x67f48ae0 | 0x6c00000 |
+| 48 | blk.3.ffn_gate_inp.weight | 0x6eb48ae0 | 0x100000 |
+| 49 | blk.3.ffn_norm.weight | 0x6ec48ae0 | 0x2000 |
+| 50 | blk.3.ffn_up_exps.weight | 0x6ec4aae0 | 0x6c00000 |
+| 51 | blk.4.attn_k.weight | 0x7584aae0 | 0x90000 |
+| 52 | blk.4.attn_k_norm.weight | 0x758daae0 | 0x200 |
+| 53 | blk.4.attn_norm.weight | 0x758dace0 | 0x2000 |
+| 54 | blk.4.attn_output.weight | 0x758dcce0 | 0x580000 |
+| 55 | blk.4.attn_q.weight | 0x75e5cce0 | 0x480000 |
+| 56 | blk.4.attn_q_norm.weight | 0x762dcce0 | 0x200 |
+| 57 | blk.4.attn_v.weight | 0x762dcee0 | 0xb0000 |
+| 58 | blk.4.ffn_down_exps.weight | 0x7638cee0 | 0x9d80000 |
+| 59 | blk.4.ffn_gate_exps.weight | 0x8010cee0 | 0x6c00000 |
+| 60 | blk.4.ffn_gate_inp.weight | 0x86d0cee0 | 0x100000 |
+| 61 | blk.4.ffn_norm.weight | 0x86e0cee0 | 0x2000 |
+| 62 | blk.4.ffn_up_exps.weight | 0x86e0eee0 | 0x6c00000 |
+| 63 | blk.5.attn_k.weight | 0x8da0eee0 | 0x90000 |
+| 64 | blk.5.attn_k_norm.weight | 0x8da9eee0 | 0x200 |
+| 65 | blk.5.attn_norm.weight | 0x8da9f0e0 | 0x2000 |
+| 66 | blk.5.attn_output.weight | 0x8daa10e0 | 0x580000 |
+| 67 | blk.5.attn_q.weight | 0x8e0210e0 | 0x480000 |
+| 68 | blk.5.attn_q_norm.weight | 0x8e4a10e0 | 0x200 |
+| 69 | blk.5.attn_v.weight | 0x8e4a12e0 | 0xd2000 |
+| 70 | blk.5.ffn_down_exps.weight | 0x8e5732e0 | 0x9d80000 |
+| 71 | blk.5.ffn_gate_exps.weight | 0x982f32e0 | 0x6c00000 |
+| 72 | blk.5.ffn_gate_inp.weight | 0x9eef32e0 | 0x100000 |
+| 73 | blk.5.ffn_norm.weight | 0x9eff32e0 | 0x2000 |
+| 74 | blk.5.ffn_up_exps.weight | 0x9eff52e0 | 0x6c00000 |
+| 75 | blk.6.attn_k.weight | 0xa5bf52e0 | 0x90000 |
+| 76 | blk.6.attn_k_norm.weight | 0xa5c852e0 | 0x200 |
+| 77 | blk.6.attn_norm.weight | 0xa5c854e0 | 0x2000 |
+| 78 | blk.6.attn_output.weight | 0xa5c874e0 | 0x580000 |
+| 79 | blk.6.attn_q.weight | 0xa62074e0 | 0x480000 |
+| 80 | blk.6.attn_q_norm.weight | 0xa66874e0 | 0x200 |
+| 81 | blk.6.attn_v.weight | 0xa66876e0 | 0xd2000 |
+| 82 | blk.6.ffn_down_exps.weight | 0xa67596e0 | 0x9d80000 |
+| 83 | blk.6.ffn_gate_exps.weight | 0xb04d96e0 | 0x6c00000 |
+| 84 | blk.6.ffn_gate_inp.weight | 0xb70d96e0 | 0x100000 |
+| 85 | blk.6.ffn_norm.weight | 0xb71d96e0 | 0x2000 |
+| 86 | blk.6.ffn_up_exps.weight | 0xb71db6e0 | 0x6c00000 |
+| 87 | blk.7.attn_k.weight | 0xbdddb6e0 | 0x90000 |
+| 88 | blk.7.attn_k_norm.weight | 0xbde6b6e0 | 0x200 |
+| 89 | blk.7.attn_norm.weight | 0xbde6b8e0 | 0x2000 |
+| 90 | blk.7.attn_output.weight | 0xbde6d8e0 | 0x580000 |
+| 91 | blk.7.attn_q.weight | 0xbe3ed8e0 | 0x480000 |
+| 92 | blk.7.attn_q_norm.weight | 0xbe86d8e0 | 0x200 |
+| 93 | blk.7.attn_v.weight | 0xbe86dae0 | 0xb0000 |
+| 94 | blk.7.ffn_down_exps.weight | 0xbe91dae0 | 0x9d80000 |
+| 95 | blk.7.ffn_gate_exps.weight | 0xc869dae0 | 0x6c00000 |
+| 96 | blk.7.ffn_gate_inp.weight | 0xcf29dae0 | 0x100000 |
+| 97 | blk.7.ffn_norm.weight | 0xcf39dae0 | 0x2000 |
+| 98 | blk.7.ffn_up_exps.weight | 0xcf39fae0 | 0x6c00000 |
+| 99 | blk.8.attn_k.weight | 0xd5f9fae0 | 0x90000 |
+| 100 | blk.8.attn_k_norm.weight | 0xd602fae0 | 0x200 |
+| 101 | blk.8.attn_norm.weight | 0xd602fce0 | 0x2000 |
+| 102 | blk.8.attn_output.weight | 0xd6031ce0 | 0x580000 |
+| 103 | blk.8.attn_q.weight | 0xd65b1ce0 | 0x480000 |
+| 104 | blk.8.attn_q_norm.weight | 0xd6a31ce0 | 0x200 |
+| 105 | blk.8.attn_v.weight | 0xd6a31ee0 | 0xd2000 |
+| 106 | blk.8.ffn_down_exps.weight | 0xd6b03ee0 | 0x9d80000 |
+| 107 | blk.8.ffn_gate_exps.weight | 0xe0883ee0 | 0x6c00000 |
+| 108 | blk.8.ffn_gate_inp.weight | 0xe7483ee0 | 0x100000 |
+| 109 | blk.8.ffn_norm.weight | 0xe7583ee0 | 0x2000 |
+| 110 | blk.8.ffn_up_exps.weight | 0xe7585ee0 | 0x6c00000 |
+| 111 | blk.9.attn_k.weight | 0xee185ee0 | 0x90000 |
+| 112 | blk.9.attn_k_norm.weight | 0xee215ee0 | 0x200 |
+| 113 | blk.9.attn_norm.weight | 0xee2160e0 | 0x2000 |
+| 114 | blk.9.attn_output.weight | 0xee2180e0 | 0x580000 |
+| 115 | blk.9.attn_q.weight | 0xee7980e0 | 0x480000 |
+| 116 | blk.9.attn_q_norm.weight | 0xeec180e0 | 0x200 |
+| 117 | blk.9.attn_v.weight | 0xeec182e0 | 0xd2000 |
+| 118 | blk.9.ffn_down_exps.weight | 0xeecea2e0 | 0x9d80000 |
+| 119 | blk.9.ffn_gate_exps.weight | 0xf8a6a2e0 | 0x6c00000 |
+| 120 | blk.9.ffn_gate_inp.weight | 0xff66a2e0 | 0x100000 |
+| 121 | blk.9.ffn_norm.weight | 0xff76a2e0 | 0x2000 |
+| 122 | blk.9.ffn_up_exps.weight | 0xff76c2e0 | 0x6c00000 |
+| 123 | blk.10.attn_k.weight | 0x10636c2e0 | 0x90000 |
+| 124 | blk.10.attn_k_norm.weight | 0x1063fc2e0 | 0x200 |
+| 125 | blk.10.attn_norm.weight | 0x1063fc4e0 | 0x2000 |
+| 126 | blk.10.attn_output.weight | 0x1063fe4e0 | 0x580000 |
+| 127 | blk.10.attn_q.weight | 0x10697e4e0 | 0x480000 |
+| 128 | blk.10.attn_q_norm.weight | 0x106dfe4e0 | 0x200 |
+| 129 | blk.10.attn_v.weight | 0x106dfe6e0 | 0xb0000 |
+| 130 | blk.10.ffn_down_exps.weight | 0x106eae6e0 | 0x9d80000 |
+| 131 | blk.10.ffn_gate_exps.weight | 0x110c2e6e0 | 0x6c00000 |
+| 132 | blk.10.ffn_gate_inp.weight | 0x11782e6e0 | 0x100000 |
+| 133 | blk.10.ffn_norm.weight | 0x11792e6e0 | 0x2000 |
+| 134 | blk.10.ffn_up_exps.weight | 0x1179306e0 | 0x6c00000 |
+| 135 | blk.11.attn_k.weight | 0x11e5306e0 | 0x90000 |
+| 136 | blk.11.attn_k_norm.weight | 0x11e5c06e0 | 0x200 |
+| 137 | blk.11.attn_norm.weight | 0x11e5c08e0 | 0x2000 |
+| 138 | blk.11.attn_output.weight | 0x11e5c28e0 | 0x580000 |
+| 139 | blk.11.attn_q.weight | 0x11eb428e0 | 0x480000 |
+| 140 | blk.11.attn_q_norm.weight | 0x11efc28e0 | 0x200 |
+| 141 | blk.11.attn_v.weight | 0x11efc2ae0 | 0xd2000 |
+| 142 | blk.11.ffn_down_exps.weight | 0x11f094ae0 | 0x9d80000 |
+| 143 | blk.11.ffn_gate_exps.weight | 0x128e14ae0 | 0x6c00000 |
+| 144 | blk.11.ffn_gate_inp.weight | 0x12fa14ae0 | 0x100000 |
+| 145 | blk.11.ffn_norm.weight | 0x12fb14ae0 | 0x2000 |
+| 146 | blk.11.ffn_up_exps.weight | 0x12fb16ae0 | 0x6c00000 |
+| 147 | blk.12.attn_k.weight | 0x136716ae0 | 0x90000 |
+| 148 | blk.12.attn_k_norm.weight | 0x1367a6ae0 | 0x200 |
+| 149 | blk.12.attn_norm.weight | 0x1367a6ce0 | 0x2000 |
+| 150 | blk.12.attn_output.weight | 0x1367a8ce0 | 0x580000 |
+| 151 | blk.12.attn_q.weight | 0x136d28ce0 | 0x480000 |
+| 152 | blk.12.attn_q_norm.weight | 0x1371a8ce0 | 0x200 |
+| 153 | blk.12.attn_v.weight | 0x1371a8ee0 | 0xd2000 |
+| 154 | blk.12.ffn_down_exps.weight | 0x13727aee0 | 0x9d80000 |
+| 155 | blk.12.ffn_gate_exps.weight | 0x140ffaee0 | 0x6c00000 |
+| 156 | blk.12.ffn_gate_inp.weight | 0x147bfaee0 | 0x100000 |
+| 157 | blk.12.ffn_norm.weight | 0x147cfaee0 | 0x2000 |
+| 158 | blk.12.ffn_up_exps.weight | 0x147cfcee0 | 0x6c00000 |
+| 159 | blk.13.attn_k.weight | 0x14e8fcee0 | 0x90000 |
+| 160 | blk.13.attn_k_norm.weight | 0x14e98cee0 | 0x200 |
+| 161 | blk.13.attn_norm.weight | 0x14e98d0e0 | 0x2000 |
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+| 413 | blk.34.attn_norm.weight | 0x3490824e0 | 0x2000 |
+| 414 | blk.34.attn_output.weight | 0x3490844e0 | 0x580000 |
+| 415 | blk.34.attn_q.weight | 0x3496044e0 | 0x480000 |
+| 416 | blk.34.attn_q_norm.weight | 0x349a844e0 | 0x200 |
+| 417 | blk.34.attn_v.weight | 0x349a846e0 | 0xb0000 |
+| 418 | blk.34.ffn_down_exps.weight | 0x349b346e0 | 0x9d80000 |
+| 419 | blk.34.ffn_gate_exps.weight | 0x3538b46e0 | 0x6c00000 |
+| 420 | blk.34.ffn_gate_inp.weight | 0x35a4b46e0 | 0x100000 |
+| 421 | blk.34.ffn_norm.weight | 0x35a5b46e0 | 0x2000 |
+| 422 | blk.34.ffn_up_exps.weight | 0x35a5b66e0 | 0x6c00000 |
+| 423 | blk.35.attn_k.weight | 0x3611b66e0 | 0x90000 |
+| 424 | blk.35.attn_k_norm.weight | 0x3612466e0 | 0x200 |
+| 425 | blk.35.attn_norm.weight | 0x3612468e0 | 0x2000 |
+| 426 | blk.35.attn_output.weight | 0x3612488e0 | 0x580000 |
+| 427 | blk.35.attn_q.weight | 0x3617c88e0 | 0x480000 |
+| 428 | blk.35.attn_q_norm.weight | 0x361c488e0 | 0x200 |
+| 429 | blk.35.attn_v.weight | 0x361c48ae0 | 0xd2000 |
+| 430 | blk.35.ffn_down_exps.weight | 0x361d1aae0 | 0x9d80000 |
+| 431 | blk.35.ffn_gate_exps.weight | 0x36ba9aae0 | 0x6c00000 |
+| 432 | blk.35.ffn_gate_inp.weight | 0x37269aae0 | 0x100000 |
+| 433 | blk.35.ffn_norm.weight | 0x37279aae0 | 0x2000 |
+| 434 | blk.35.ffn_up_exps.weight | 0x37279cae0 | 0x6c00000 |
+| 435 | blk.36.attn_k.weight | 0x37939cae0 | 0xb0000 |
+| 436 | blk.36.attn_k_norm.weight | 0x37944cae0 | 0x200 |
+| 437 | blk.36.attn_norm.weight | 0x37944cce0 | 0x2000 |
+| 438 | blk.36.attn_output.weight | 0x37944ece0 | 0x580000 |
+| 439 | blk.36.attn_q.weight | 0x3799cece0 | 0x580000 |
+| 440 | blk.36.attn_q_norm.weight | 0x379f4ece0 | 0x200 |
+| 441 | blk.36.attn_v.weight | 0x379f4eee0 | 0xd2000 |
+| 442 | blk.36.ffn_down_exps.weight | 0x37a020ee0 | 0x9d80000 |
+| 443 | blk.36.ffn_gate_exps.weight | 0x383da0ee0 | 0x8400000 |
+| 444 | blk.36.ffn_gate_inp.weight | 0x38c1a0ee0 | 0x100000 |
+| 445 | blk.36.ffn_norm.weight | 0x38c2a0ee0 | 0x2000 |
+| 446 | blk.36.ffn_up_exps.weight | 0x38c2a2ee0 | 0x8400000 |
+| 447 | blk.37.attn_k.weight | 0x3946a2ee0 | 0xb0000 |
+| 448 | blk.37.attn_k_norm.weight | 0x394752ee0 | 0x200 |
+| 449 | blk.37.attn_norm.weight | 0x3947530e0 | 0x2000 |
+| 450 | blk.37.attn_output.weight | 0x3947550e0 | 0x580000 |
+| 451 | blk.37.attn_q.weight | 0x394cd50e0 | 0x580000 |
+| 452 | blk.37.attn_q_norm.weight | 0x3952550e0 | 0x200 |
+| 453 | blk.37.attn_v.weight | 0x3952552e0 | 0xd2000 |
+| 454 | blk.37.ffn_down_exps.weight | 0x3953272e0 | 0x9d80000 |
+| 455 | blk.37.ffn_gate_exps.weight | 0x39f0a72e0 | 0x8400000 |
+| 456 | blk.37.ffn_gate_inp.weight | 0x3a74a72e0 | 0x100000 |
+| 457 | blk.37.ffn_norm.weight | 0x3a75a72e0 | 0x2000 |
+| 458 | blk.37.ffn_up_exps.weight | 0x3a75a92e0 | 0x8400000 |
+| 459 | blk.38.attn_k.weight | 0x3af9a92e0 | 0xb0000 |
+| 460 | blk.38.attn_k_norm.weight | 0x3afa592e0 | 0x200 |
+| 461 | blk.38.attn_norm.weight | 0x3afa594e0 | 0x2000 |
+| 462 | blk.38.attn_output.weight | 0x3afa5b4e0 | 0x580000 |
+| 463 | blk.38.attn_q.weight | 0x3affdb4e0 | 0x580000 |
+| 464 | blk.38.attn_q_norm.weight | 0x3b055b4e0 | 0x200 |
+| 465 | blk.38.attn_v.weight | 0x3b055b6e0 | 0xd2000 |
+| 466 | blk.38.ffn_down_exps.weight | 0x3b062d6e0 | 0x9d80000 |
+| 467 | blk.38.ffn_gate_exps.weight | 0x3ba3ad6e0 | 0x8400000 |
+| 468 | blk.38.ffn_gate_inp.weight | 0x3c27ad6e0 | 0x100000 |
+| 469 | blk.38.ffn_norm.weight | 0x3c28ad6e0 | 0x2000 |
+| 470 | blk.38.ffn_up_exps.weight | 0x3c28af6e0 | 0x8400000 |
+| 471 | blk.39.attn_k.weight | 0x3cacaf6e0 | 0xb0000 |
+| 472 | blk.39.attn_k_norm.weight | 0x3cad5f6e0 | 0x200 |
+| 473 | blk.39.attn_norm.weight | 0x3cad5f8e0 | 0x2000 |
+| 474 | blk.39.attn_output.weight | 0x3cad618e0 | 0x580000 |
+| 475 | blk.39.attn_q.weight | 0x3cb2e18e0 | 0x580000 |
+| 476 | blk.39.attn_q_norm.weight | 0x3cb8618e0 | 0x200 |
+| 477 | blk.39.attn_v.weight | 0x3cb861ae0 | 0xd2000 |
+| 478 | blk.39.ffn_down_exps.weight | 0x3cb933ae0 | 0x9d80000 |
+| 479 | blk.39.ffn_gate_exps.weight | 0x3d56b3ae0 | 0x8400000 |
+| 480 | blk.39.ffn_gate_inp.weight | 0x3ddab3ae0 | 0x100000 |
+| 481 | blk.39.ffn_norm.weight | 0x3ddbb3ae0 | 0x2000 |
+| 482 | blk.39.ffn_up_exps.weight | 0x3ddbb5ae0 | 0x8400000 |
+| 483 | blk.40.attn_k.weight | 0x3e5fb5ae0 | 0xb0000 |
+| 484 | blk.40.attn_k_norm.weight | 0x3e6065ae0 | 0x200 |
+| 485 | blk.40.attn_norm.weight | 0x3e6065ce0 | 0x2000 |
+| 486 | blk.40.attn_output.weight | 0x3e6067ce0 | 0x580000 |
+| 487 | blk.40.attn_q.weight | 0x3e65e7ce0 | 0x580000 |
+| 488 | blk.40.attn_q_norm.weight | 0x3e6b67ce0 | 0x200 |
+| 489 | blk.40.attn_v.weight | 0x3e6b67ee0 | 0xd2000 |
+| 490 | blk.40.ffn_down_exps.weight | 0x3e6c39ee0 | 0x9d80000 |
+| 491 | blk.40.ffn_gate_exps.weight | 0x3f09b9ee0 | 0x8400000 |
+| 492 | blk.40.ffn_gate_inp.weight | 0x3f8db9ee0 | 0x100000 |
+| 493 | blk.40.ffn_norm.weight | 0x3f8eb9ee0 | 0x2000 |
+| 494 | blk.40.ffn_up_exps.weight | 0x3f8ebbee0 | 0x8400000 |
+| 495 | blk.41.attn_k.weight | 0x4012bbee0 | 0xb0000 |
+| 496 | blk.41.attn_k_norm.weight | 0x40136bee0 | 0x200 |
+| 497 | blk.41.attn_norm.weight | 0x40136c0e0 | 0x2000 |
+| 498 | blk.41.attn_output.weight | 0x40136e0e0 | 0x580000 |
+| 499 | blk.41.attn_q.weight | 0x4018ee0e0 | 0x580000 |
+| 500 | blk.41.attn_q_norm.weight | 0x401e6e0e0 | 0x200 |
+| 501 | blk.41.attn_v.weight | 0x401e6e2e0 | 0xd2000 |
+| 502 | blk.41.ffn_down_exps.weight | 0x401f402e0 | 0x9d80000 |
+| 503 | blk.41.ffn_gate_exps.weight | 0x40bcc02e0 | 0x8400000 |
+| 504 | blk.41.ffn_gate_inp.weight | 0x4140c02e0 | 0x100000 |
+| 505 | blk.41.ffn_norm.weight | 0x4141c02e0 | 0x2000 |
+| 506 | blk.41.ffn_up_exps.weight | 0x4141c22e0 | 0x8400000 |
+| 507 | blk.42.attn_k.weight | 0x41c5c22e0 | 0xb0000 |
+| 508 | blk.42.attn_k_norm.weight | 0x41c6722e0 | 0x200 |
+| 509 | blk.42.attn_norm.weight | 0x41c6724e0 | 0x2000 |
+| 510 | blk.42.attn_output.weight | 0x41c6744e0 | 0x580000 |
+| 511 | blk.42.attn_q.weight | 0x41cbf44e0 | 0x580000 |
+| 512 | blk.42.attn_q_norm.weight | 0x41d1744e0 | 0x200 |
+| 513 | blk.42.attn_v.weight | 0x41d1746e0 | 0xd2000 |
+| 514 | blk.42.ffn_down_exps.weight | 0x41d2466e0 | 0x9d80000 |
+| 515 | blk.42.ffn_gate_exps.weight | 0x426fc66e0 | 0x8400000 |
+| 516 | blk.42.ffn_gate_inp.weight | 0x42f3c66e0 | 0x100000 |
+| 517 | blk.42.ffn_norm.weight | 0x42f4c66e0 | 0x2000 |
+| 518 | blk.42.ffn_up_exps.weight | 0x42f4c86e0 | 0x8400000 |
+| 519 | blk.43.attn_k.weight | 0x4378c86e0 | 0xb0000 |
+| 520 | blk.43.attn_k_norm.weight | 0x4379786e0 | 0x200 |
+| 521 | blk.43.attn_norm.weight | 0x4379788e0 | 0x2000 |
+| 522 | blk.43.attn_output.weight | 0x43797a8e0 | 0x580000 |
+| 523 | blk.43.attn_q.weight | 0x437efa8e0 | 0x580000 |
+| 524 | blk.43.attn_q_norm.weight | 0x43847a8e0 | 0x200 |
+| 525 | blk.43.attn_v.weight | 0x43847aae0 | 0xd2000 |
+| 526 | blk.43.ffn_down_exps.weight | 0x43854cae0 | 0x9d80000 |
+| 527 | blk.43.ffn_gate_exps.weight | 0x4422ccae0 | 0x8400000 |
+| 528 | blk.43.ffn_gate_inp.weight | 0x44a6ccae0 | 0x100000 |
+| 529 | blk.43.ffn_norm.weight | 0x44a7ccae0 | 0x2000 |
+| 530 | blk.43.ffn_up_exps.weight | 0x44a7ceae0 | 0x8400000 |
+| 531 | blk.44.attn_k.weight | 0x452bceae0 | 0xb0000 |
+| 532 | blk.44.attn_k_norm.weight | 0x452c7eae0 | 0x200 |
+| 533 | blk.44.attn_norm.weight | 0x452c7ece0 | 0x2000 |
+| 534 | blk.44.attn_output.weight | 0x452c80ce0 | 0x580000 |
+| 535 | blk.44.attn_q.weight | 0x453200ce0 | 0x580000 |
+| 536 | blk.44.attn_q_norm.weight | 0x453780ce0 | 0x200 |
+| 537 | blk.44.attn_v.weight | 0x453780ee0 | 0xd2000 |
+| 538 | blk.44.ffn_down_exps.weight | 0x453852ee0 | 0x9d80000 |
+| 539 | blk.44.ffn_gate_exps.weight | 0x45d5d2ee0 | 0x8400000 |
+| 540 | blk.44.ffn_gate_inp.weight | 0x4659d2ee0 | 0x100000 |
+| 541 | blk.44.ffn_norm.weight | 0x465ad2ee0 | 0x2000 |
+| 542 | blk.44.ffn_up_exps.weight | 0x465ad4ee0 | 0x8400000 |
+| 543 | blk.45.attn_k.weight | 0x46ded4ee0 | 0xb0000 |
+| 544 | blk.45.attn_k_norm.weight | 0x46df84ee0 | 0x200 |
+| 545 | blk.45.attn_norm.weight | 0x46df850e0 | 0x2000 |
+| 546 | blk.45.attn_output.weight | 0x46df870e0 | 0x580000 |
+| 547 | blk.45.attn_q.weight | 0x46e5070e0 | 0x580000 |
+| 548 | blk.45.attn_q_norm.weight | 0x46ea870e0 | 0x200 |
+| 549 | blk.45.attn_v.weight | 0x46ea872e0 | 0xd2000 |
+| 550 | blk.45.ffn_down_exps.weight | 0x46eb592e0 | 0x9d80000 |
+| 551 | blk.45.ffn_gate_exps.weight | 0x4788d92e0 | 0x8400000 |
+| 552 | blk.45.ffn_gate_inp.weight | 0x480cd92e0 | 0x100000 |
+| 553 | blk.45.ffn_norm.weight | 0x480dd92e0 | 0x2000 |
+| 554 | blk.45.ffn_up_exps.weight | 0x480ddb2e0 | 0x8400000 |
+
+### Base Tensor Group : ~622M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+| 0 | output.weight | Output (W) | (~311M) 311164928 | 2048 x 151936 x 1 x 1 | Q5_K |
+| 1 | output_norm.weight | Output Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 2 | token_embd.weight | Token Embedding (W) | (~311M) 311164928 | 2048 x 151936 x 1 x 1 | Q3_K |
+
+- Total elements in base: (~622M) 622331904
+- Percentage of total elements: 2.13%
+
+
+### Block 0 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:---------------------------|:------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 3 | blk.0.attn_k.weight | Block 0 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 4 | blk.0.attn_k_norm.weight | Block 0 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 5 | blk.0.attn_norm.weight | Block 0 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 6 | blk.0.attn_output.weight | Block 0 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 7 | blk.0.attn_q.weight | Block 0 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 8 | blk.0.attn_q_norm.weight | Block 0 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 9 | blk.0.attn_v.weight | Block 0 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 10 | blk.0.ffn_down_exps.weight | Block 0 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 11 | blk.0.ffn_gate_exps.weight | Block 0 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 12 | blk.0.ffn_gate_inp.weight | Block 0 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 13 | blk.0.ffn_norm.weight | Block 0 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 14 | blk.0.ffn_up_exps.weight | Block 0 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.0: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 1 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:---------------------------|:------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 15 | blk.1.attn_k.weight | Block 1 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 16 | blk.1.attn_k_norm.weight | Block 1 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 17 | blk.1.attn_norm.weight | Block 1 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 18 | blk.1.attn_output.weight | Block 1 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 19 | blk.1.attn_q.weight | Block 1 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 20 | blk.1.attn_q_norm.weight | Block 1 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 21 | blk.1.attn_v.weight | Block 1 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 22 | blk.1.ffn_down_exps.weight | Block 1 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 23 | blk.1.ffn_gate_exps.weight | Block 1 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 24 | blk.1.ffn_gate_inp.weight | Block 1 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 25 | blk.1.ffn_norm.weight | Block 1 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 26 | blk.1.ffn_up_exps.weight | Block 1 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.1: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 2 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:---------------------------|:------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 27 | blk.2.attn_k.weight | Block 2 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 28 | blk.2.attn_k_norm.weight | Block 2 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 29 | blk.2.attn_norm.weight | Block 2 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 30 | blk.2.attn_output.weight | Block 2 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 31 | blk.2.attn_q.weight | Block 2 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 32 | blk.2.attn_q_norm.weight | Block 2 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 33 | blk.2.attn_v.weight | Block 2 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 34 | blk.2.ffn_down_exps.weight | Block 2 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 35 | blk.2.ffn_gate_exps.weight | Block 2 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 36 | blk.2.ffn_gate_inp.weight | Block 2 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 37 | blk.2.ffn_norm.weight | Block 2 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 38 | blk.2.ffn_up_exps.weight | Block 2 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.2: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 3 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:---------------------------|:------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 39 | blk.3.attn_k.weight | Block 3 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 40 | blk.3.attn_k_norm.weight | Block 3 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 41 | blk.3.attn_norm.weight | Block 3 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 42 | blk.3.attn_output.weight | Block 3 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 43 | blk.3.attn_q.weight | Block 3 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 44 | blk.3.attn_q_norm.weight | Block 3 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 45 | blk.3.attn_v.weight | Block 3 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 46 | blk.3.ffn_down_exps.weight | Block 3 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 47 | blk.3.ffn_gate_exps.weight | Block 3 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 48 | blk.3.ffn_gate_inp.weight | Block 3 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 49 | blk.3.ffn_norm.weight | Block 3 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 50 | blk.3.ffn_up_exps.weight | Block 3 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.3: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 4 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:---------------------------|:------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 51 | blk.4.attn_k.weight | Block 4 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 52 | blk.4.attn_k_norm.weight | Block 4 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 53 | blk.4.attn_norm.weight | Block 4 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 54 | blk.4.attn_output.weight | Block 4 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 55 | blk.4.attn_q.weight | Block 4 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 56 | blk.4.attn_q_norm.weight | Block 4 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 57 | blk.4.attn_v.weight | Block 4 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 58 | blk.4.ffn_down_exps.weight | Block 4 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 59 | blk.4.ffn_gate_exps.weight | Block 4 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 60 | blk.4.ffn_gate_inp.weight | Block 4 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 61 | blk.4.ffn_norm.weight | Block 4 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 62 | blk.4.ffn_up_exps.weight | Block 4 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.4: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 5 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:---------------------------|:------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 63 | blk.5.attn_k.weight | Block 5 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 64 | blk.5.attn_k_norm.weight | Block 5 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 65 | blk.5.attn_norm.weight | Block 5 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 66 | blk.5.attn_output.weight | Block 5 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 67 | blk.5.attn_q.weight | Block 5 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 68 | blk.5.attn_q_norm.weight | Block 5 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 69 | blk.5.attn_v.weight | Block 5 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 70 | blk.5.ffn_down_exps.weight | Block 5 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 71 | blk.5.ffn_gate_exps.weight | Block 5 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 72 | blk.5.ffn_gate_inp.weight | Block 5 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 73 | blk.5.ffn_norm.weight | Block 5 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 74 | blk.5.ffn_up_exps.weight | Block 5 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.5: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 6 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:---------------------------|:------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 75 | blk.6.attn_k.weight | Block 6 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 76 | blk.6.attn_k_norm.weight | Block 6 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 77 | blk.6.attn_norm.weight | Block 6 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 78 | blk.6.attn_output.weight | Block 6 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 79 | blk.6.attn_q.weight | Block 6 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 80 | blk.6.attn_q_norm.weight | Block 6 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 81 | blk.6.attn_v.weight | Block 6 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 82 | blk.6.ffn_down_exps.weight | Block 6 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 83 | blk.6.ffn_gate_exps.weight | Block 6 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 84 | blk.6.ffn_gate_inp.weight | Block 6 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 85 | blk.6.ffn_norm.weight | Block 6 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 86 | blk.6.ffn_up_exps.weight | Block 6 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.6: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 7 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:---------------------------|:------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 87 | blk.7.attn_k.weight | Block 7 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 88 | blk.7.attn_k_norm.weight | Block 7 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 89 | blk.7.attn_norm.weight | Block 7 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 90 | blk.7.attn_output.weight | Block 7 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 91 | blk.7.attn_q.weight | Block 7 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 92 | blk.7.attn_q_norm.weight | Block 7 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 93 | blk.7.attn_v.weight | Block 7 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 94 | blk.7.ffn_down_exps.weight | Block 7 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 95 | blk.7.ffn_gate_exps.weight | Block 7 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 96 | blk.7.ffn_gate_inp.weight | Block 7 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 97 | blk.7.ffn_norm.weight | Block 7 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 98 | blk.7.ffn_up_exps.weight | Block 7 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.7: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 8 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:---------------------------|:------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 99 | blk.8.attn_k.weight | Block 8 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 100 | blk.8.attn_k_norm.weight | Block 8 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 101 | blk.8.attn_norm.weight | Block 8 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 102 | blk.8.attn_output.weight | Block 8 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 103 | blk.8.attn_q.weight | Block 8 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 104 | blk.8.attn_q_norm.weight | Block 8 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 105 | blk.8.attn_v.weight | Block 8 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 106 | blk.8.ffn_down_exps.weight | Block 8 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 107 | blk.8.ffn_gate_exps.weight | Block 8 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 108 | blk.8.ffn_gate_inp.weight | Block 8 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 109 | blk.8.ffn_norm.weight | Block 8 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 110 | blk.8.ffn_up_exps.weight | Block 8 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.8: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 9 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:---------------------------|:------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 111 | blk.9.attn_k.weight | Block 9 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 112 | blk.9.attn_k_norm.weight | Block 9 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 113 | blk.9.attn_norm.weight | Block 9 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 114 | blk.9.attn_output.weight | Block 9 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 115 | blk.9.attn_q.weight | Block 9 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 116 | blk.9.attn_q_norm.weight | Block 9 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 117 | blk.9.attn_v.weight | Block 9 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 118 | blk.9.ffn_down_exps.weight | Block 9 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 119 | blk.9.ffn_gate_exps.weight | Block 9 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 120 | blk.9.ffn_gate_inp.weight | Block 9 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 121 | blk.9.ffn_norm.weight | Block 9 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 122 | blk.9.ffn_up_exps.weight | Block 9 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.9: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 10 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 123 | blk.10.attn_k.weight | Block 10 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 124 | blk.10.attn_k_norm.weight | Block 10 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 125 | blk.10.attn_norm.weight | Block 10 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 126 | blk.10.attn_output.weight | Block 10 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 127 | blk.10.attn_q.weight | Block 10 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 128 | blk.10.attn_q_norm.weight | Block 10 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 129 | blk.10.attn_v.weight | Block 10 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 130 | blk.10.ffn_down_exps.weight | Block 10 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 131 | blk.10.ffn_gate_exps.weight | Block 10 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 132 | blk.10.ffn_gate_inp.weight | Block 10 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 133 | blk.10.ffn_norm.weight | Block 10 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 134 | blk.10.ffn_up_exps.weight | Block 10 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.10: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 11 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 135 | blk.11.attn_k.weight | Block 11 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 136 | blk.11.attn_k_norm.weight | Block 11 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 137 | blk.11.attn_norm.weight | Block 11 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 138 | blk.11.attn_output.weight | Block 11 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 139 | blk.11.attn_q.weight | Block 11 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 140 | blk.11.attn_q_norm.weight | Block 11 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 141 | blk.11.attn_v.weight | Block 11 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 142 | blk.11.ffn_down_exps.weight | Block 11 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 143 | blk.11.ffn_gate_exps.weight | Block 11 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 144 | blk.11.ffn_gate_inp.weight | Block 11 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 145 | blk.11.ffn_norm.weight | Block 11 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 146 | blk.11.ffn_up_exps.weight | Block 11 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.11: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 12 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 147 | blk.12.attn_k.weight | Block 12 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 148 | blk.12.attn_k_norm.weight | Block 12 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 149 | blk.12.attn_norm.weight | Block 12 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 150 | blk.12.attn_output.weight | Block 12 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 151 | blk.12.attn_q.weight | Block 12 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 152 | blk.12.attn_q_norm.weight | Block 12 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 153 | blk.12.attn_v.weight | Block 12 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 154 | blk.12.ffn_down_exps.weight | Block 12 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 155 | blk.12.ffn_gate_exps.weight | Block 12 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 156 | blk.12.ffn_gate_inp.weight | Block 12 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 157 | blk.12.ffn_norm.weight | Block 12 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 158 | blk.12.ffn_up_exps.weight | Block 12 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.12: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 13 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 159 | blk.13.attn_k.weight | Block 13 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 160 | blk.13.attn_k_norm.weight | Block 13 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 161 | blk.13.attn_norm.weight | Block 13 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 162 | blk.13.attn_output.weight | Block 13 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 163 | blk.13.attn_q.weight | Block 13 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 164 | blk.13.attn_q_norm.weight | Block 13 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 165 | blk.13.attn_v.weight | Block 13 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 166 | blk.13.ffn_down_exps.weight | Block 13 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 167 | blk.13.ffn_gate_exps.weight | Block 13 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 168 | blk.13.ffn_gate_inp.weight | Block 13 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 169 | blk.13.ffn_norm.weight | Block 13 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 170 | blk.13.ffn_up_exps.weight | Block 13 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.13: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 14 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 171 | blk.14.attn_k.weight | Block 14 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 172 | blk.14.attn_k_norm.weight | Block 14 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 173 | blk.14.attn_norm.weight | Block 14 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 174 | blk.14.attn_output.weight | Block 14 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 175 | blk.14.attn_q.weight | Block 14 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 176 | blk.14.attn_q_norm.weight | Block 14 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 177 | blk.14.attn_v.weight | Block 14 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 178 | blk.14.ffn_down_exps.weight | Block 14 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 179 | blk.14.ffn_gate_exps.weight | Block 14 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 180 | blk.14.ffn_gate_inp.weight | Block 14 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 181 | blk.14.ffn_norm.weight | Block 14 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 182 | blk.14.ffn_up_exps.weight | Block 14 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.14: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 15 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 183 | blk.15.attn_k.weight | Block 15 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 184 | blk.15.attn_k_norm.weight | Block 15 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 185 | blk.15.attn_norm.weight | Block 15 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 186 | blk.15.attn_output.weight | Block 15 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 187 | blk.15.attn_q.weight | Block 15 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 188 | blk.15.attn_q_norm.weight | Block 15 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 189 | blk.15.attn_v.weight | Block 15 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 190 | blk.15.ffn_down_exps.weight | Block 15 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 191 | blk.15.ffn_gate_exps.weight | Block 15 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 192 | blk.15.ffn_gate_inp.weight | Block 15 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 193 | blk.15.ffn_norm.weight | Block 15 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 194 | blk.15.ffn_up_exps.weight | Block 15 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.15: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 16 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 195 | blk.16.attn_k.weight | Block 16 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 196 | blk.16.attn_k_norm.weight | Block 16 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 197 | blk.16.attn_norm.weight | Block 16 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 198 | blk.16.attn_output.weight | Block 16 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 199 | blk.16.attn_q.weight | Block 16 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 200 | blk.16.attn_q_norm.weight | Block 16 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 201 | blk.16.attn_v.weight | Block 16 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 202 | blk.16.ffn_down_exps.weight | Block 16 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 203 | blk.16.ffn_gate_exps.weight | Block 16 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 204 | blk.16.ffn_gate_inp.weight | Block 16 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 205 | blk.16.ffn_norm.weight | Block 16 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 206 | blk.16.ffn_up_exps.weight | Block 16 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.16: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 17 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 207 | blk.17.attn_k.weight | Block 17 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 208 | blk.17.attn_k_norm.weight | Block 17 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 209 | blk.17.attn_norm.weight | Block 17 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 210 | blk.17.attn_output.weight | Block 17 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 211 | blk.17.attn_q.weight | Block 17 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 212 | blk.17.attn_q_norm.weight | Block 17 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 213 | blk.17.attn_v.weight | Block 17 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 214 | blk.17.ffn_down_exps.weight | Block 17 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 215 | blk.17.ffn_gate_exps.weight | Block 17 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 216 | blk.17.ffn_gate_inp.weight | Block 17 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 217 | blk.17.ffn_norm.weight | Block 17 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 218 | blk.17.ffn_up_exps.weight | Block 17 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.17: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 18 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 219 | blk.18.attn_k.weight | Block 18 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 220 | blk.18.attn_k_norm.weight | Block 18 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 221 | blk.18.attn_norm.weight | Block 18 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 222 | blk.18.attn_output.weight | Block 18 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 223 | blk.18.attn_q.weight | Block 18 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 224 | blk.18.attn_q_norm.weight | Block 18 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 225 | blk.18.attn_v.weight | Block 18 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 226 | blk.18.ffn_down_exps.weight | Block 18 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 227 | blk.18.ffn_gate_exps.weight | Block 18 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 228 | blk.18.ffn_gate_inp.weight | Block 18 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 229 | blk.18.ffn_norm.weight | Block 18 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 230 | blk.18.ffn_up_exps.weight | Block 18 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.18: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 19 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 231 | blk.19.attn_k.weight | Block 19 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 232 | blk.19.attn_k_norm.weight | Block 19 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 233 | blk.19.attn_norm.weight | Block 19 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 234 | blk.19.attn_output.weight | Block 19 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 235 | blk.19.attn_q.weight | Block 19 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 236 | blk.19.attn_q_norm.weight | Block 19 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 237 | blk.19.attn_v.weight | Block 19 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 238 | blk.19.ffn_down_exps.weight | Block 19 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 239 | blk.19.ffn_gate_exps.weight | Block 19 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 240 | blk.19.ffn_gate_inp.weight | Block 19 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 241 | blk.19.ffn_norm.weight | Block 19 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 242 | blk.19.ffn_up_exps.weight | Block 19 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.19: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 20 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 243 | blk.20.attn_k.weight | Block 20 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 244 | blk.20.attn_k_norm.weight | Block 20 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 245 | blk.20.attn_norm.weight | Block 20 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 246 | blk.20.attn_output.weight | Block 20 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 247 | blk.20.attn_q.weight | Block 20 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 248 | blk.20.attn_q_norm.weight | Block 20 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 249 | blk.20.attn_v.weight | Block 20 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 250 | blk.20.ffn_down_exps.weight | Block 20 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 251 | blk.20.ffn_gate_exps.weight | Block 20 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 252 | blk.20.ffn_gate_inp.weight | Block 20 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 253 | blk.20.ffn_norm.weight | Block 20 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 254 | blk.20.ffn_up_exps.weight | Block 20 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.20: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 21 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 255 | blk.21.attn_k.weight | Block 21 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 256 | blk.21.attn_k_norm.weight | Block 21 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 257 | blk.21.attn_norm.weight | Block 21 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 258 | blk.21.attn_output.weight | Block 21 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 259 | blk.21.attn_q.weight | Block 21 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 260 | blk.21.attn_q_norm.weight | Block 21 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 261 | blk.21.attn_v.weight | Block 21 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 262 | blk.21.ffn_down_exps.weight | Block 21 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 263 | blk.21.ffn_gate_exps.weight | Block 21 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 264 | blk.21.ffn_gate_inp.weight | Block 21 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 265 | blk.21.ffn_norm.weight | Block 21 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 266 | blk.21.ffn_up_exps.weight | Block 21 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.21: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 22 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 267 | blk.22.attn_k.weight | Block 22 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 268 | blk.22.attn_k_norm.weight | Block 22 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 269 | blk.22.attn_norm.weight | Block 22 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 270 | blk.22.attn_output.weight | Block 22 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 271 | blk.22.attn_q.weight | Block 22 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 272 | blk.22.attn_q_norm.weight | Block 22 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 273 | blk.22.attn_v.weight | Block 22 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 274 | blk.22.ffn_down_exps.weight | Block 22 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 275 | blk.22.ffn_gate_exps.weight | Block 22 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 276 | blk.22.ffn_gate_inp.weight | Block 22 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 277 | blk.22.ffn_norm.weight | Block 22 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 278 | blk.22.ffn_up_exps.weight | Block 22 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.22: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 23 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 279 | blk.23.attn_k.weight | Block 23 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 280 | blk.23.attn_k_norm.weight | Block 23 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 281 | blk.23.attn_norm.weight | Block 23 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 282 | blk.23.attn_output.weight | Block 23 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 283 | blk.23.attn_q.weight | Block 23 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 284 | blk.23.attn_q_norm.weight | Block 23 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 285 | blk.23.attn_v.weight | Block 23 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 286 | blk.23.ffn_down_exps.weight | Block 23 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 287 | blk.23.ffn_gate_exps.weight | Block 23 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 288 | blk.23.ffn_gate_inp.weight | Block 23 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 289 | blk.23.ffn_norm.weight | Block 23 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 290 | blk.23.ffn_up_exps.weight | Block 23 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.23: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 24 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 291 | blk.24.attn_k.weight | Block 24 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 292 | blk.24.attn_k_norm.weight | Block 24 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 293 | blk.24.attn_norm.weight | Block 24 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 294 | blk.24.attn_output.weight | Block 24 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 295 | blk.24.attn_q.weight | Block 24 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 296 | blk.24.attn_q_norm.weight | Block 24 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 297 | blk.24.attn_v.weight | Block 24 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 298 | blk.24.ffn_down_exps.weight | Block 24 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 299 | blk.24.ffn_gate_exps.weight | Block 24 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 300 | blk.24.ffn_gate_inp.weight | Block 24 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 301 | blk.24.ffn_norm.weight | Block 24 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 302 | blk.24.ffn_up_exps.weight | Block 24 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.24: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 25 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 303 | blk.25.attn_k.weight | Block 25 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 304 | blk.25.attn_k_norm.weight | Block 25 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 305 | blk.25.attn_norm.weight | Block 25 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 306 | blk.25.attn_output.weight | Block 25 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 307 | blk.25.attn_q.weight | Block 25 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 308 | blk.25.attn_q_norm.weight | Block 25 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 309 | blk.25.attn_v.weight | Block 25 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 310 | blk.25.ffn_down_exps.weight | Block 25 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 311 | blk.25.ffn_gate_exps.weight | Block 25 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 312 | blk.25.ffn_gate_inp.weight | Block 25 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 313 | blk.25.ffn_norm.weight | Block 25 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 314 | blk.25.ffn_up_exps.weight | Block 25 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.25: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 26 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 315 | blk.26.attn_k.weight | Block 26 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 316 | blk.26.attn_k_norm.weight | Block 26 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 317 | blk.26.attn_norm.weight | Block 26 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 318 | blk.26.attn_output.weight | Block 26 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 319 | blk.26.attn_q.weight | Block 26 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 320 | blk.26.attn_q_norm.weight | Block 26 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 321 | blk.26.attn_v.weight | Block 26 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 322 | blk.26.ffn_down_exps.weight | Block 26 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 323 | blk.26.ffn_gate_exps.weight | Block 26 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 324 | blk.26.ffn_gate_inp.weight | Block 26 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 325 | blk.26.ffn_norm.weight | Block 26 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 326 | blk.26.ffn_up_exps.weight | Block 26 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.26: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 27 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 327 | blk.27.attn_k.weight | Block 27 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 328 | blk.27.attn_k_norm.weight | Block 27 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 329 | blk.27.attn_norm.weight | Block 27 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 330 | blk.27.attn_output.weight | Block 27 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 331 | blk.27.attn_q.weight | Block 27 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 332 | blk.27.attn_q_norm.weight | Block 27 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 333 | blk.27.attn_v.weight | Block 27 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 334 | blk.27.ffn_down_exps.weight | Block 27 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 335 | blk.27.ffn_gate_exps.weight | Block 27 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 336 | blk.27.ffn_gate_inp.weight | Block 27 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 337 | blk.27.ffn_norm.weight | Block 27 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 338 | blk.27.ffn_up_exps.weight | Block 27 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.27: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 28 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 339 | blk.28.attn_k.weight | Block 28 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 340 | blk.28.attn_k_norm.weight | Block 28 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 341 | blk.28.attn_norm.weight | Block 28 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 342 | blk.28.attn_output.weight | Block 28 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 343 | blk.28.attn_q.weight | Block 28 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 344 | blk.28.attn_q_norm.weight | Block 28 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 345 | blk.28.attn_v.weight | Block 28 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 346 | blk.28.ffn_down_exps.weight | Block 28 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 347 | blk.28.ffn_gate_exps.weight | Block 28 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 348 | blk.28.ffn_gate_inp.weight | Block 28 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 349 | blk.28.ffn_norm.weight | Block 28 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 350 | blk.28.ffn_up_exps.weight | Block 28 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.28: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 29 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 351 | blk.29.attn_k.weight | Block 29 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 352 | blk.29.attn_k_norm.weight | Block 29 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 353 | blk.29.attn_norm.weight | Block 29 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 354 | blk.29.attn_output.weight | Block 29 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 355 | blk.29.attn_q.weight | Block 29 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 356 | blk.29.attn_q_norm.weight | Block 29 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 357 | blk.29.attn_v.weight | Block 29 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 358 | blk.29.ffn_down_exps.weight | Block 29 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 359 | blk.29.ffn_gate_exps.weight | Block 29 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 360 | blk.29.ffn_gate_inp.weight | Block 29 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 361 | blk.29.ffn_norm.weight | Block 29 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 362 | blk.29.ffn_up_exps.weight | Block 29 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.29: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 30 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 363 | blk.30.attn_k.weight | Block 30 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 364 | blk.30.attn_k_norm.weight | Block 30 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 365 | blk.30.attn_norm.weight | Block 30 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 366 | blk.30.attn_output.weight | Block 30 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 367 | blk.30.attn_q.weight | Block 30 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 368 | blk.30.attn_q_norm.weight | Block 30 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 369 | blk.30.attn_v.weight | Block 30 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 370 | blk.30.ffn_down_exps.weight | Block 30 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 371 | blk.30.ffn_gate_exps.weight | Block 30 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 372 | blk.30.ffn_gate_inp.weight | Block 30 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 373 | blk.30.ffn_norm.weight | Block 30 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 374 | blk.30.ffn_up_exps.weight | Block 30 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.30: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 31 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 375 | blk.31.attn_k.weight | Block 31 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 376 | blk.31.attn_k_norm.weight | Block 31 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 377 | blk.31.attn_norm.weight | Block 31 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 378 | blk.31.attn_output.weight | Block 31 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 379 | blk.31.attn_q.weight | Block 31 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 380 | blk.31.attn_q_norm.weight | Block 31 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 381 | blk.31.attn_v.weight | Block 31 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 382 | blk.31.ffn_down_exps.weight | Block 31 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 383 | blk.31.ffn_gate_exps.weight | Block 31 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 384 | blk.31.ffn_gate_inp.weight | Block 31 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 385 | blk.31.ffn_norm.weight | Block 31 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 386 | blk.31.ffn_up_exps.weight | Block 31 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.31: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 32 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 387 | blk.32.attn_k.weight | Block 32 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 388 | blk.32.attn_k_norm.weight | Block 32 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 389 | blk.32.attn_norm.weight | Block 32 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 390 | blk.32.attn_output.weight | Block 32 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 391 | blk.32.attn_q.weight | Block 32 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 392 | blk.32.attn_q_norm.weight | Block 32 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 393 | blk.32.attn_v.weight | Block 32 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 394 | blk.32.ffn_down_exps.weight | Block 32 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 395 | blk.32.ffn_gate_exps.weight | Block 32 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 396 | blk.32.ffn_gate_inp.weight | Block 32 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 397 | blk.32.ffn_norm.weight | Block 32 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 398 | blk.32.ffn_up_exps.weight | Block 32 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.32: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 33 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 399 | blk.33.attn_k.weight | Block 33 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 400 | blk.33.attn_k_norm.weight | Block 33 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 401 | blk.33.attn_norm.weight | Block 33 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 402 | blk.33.attn_output.weight | Block 33 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 403 | blk.33.attn_q.weight | Block 33 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 404 | blk.33.attn_q_norm.weight | Block 33 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 405 | blk.33.attn_v.weight | Block 33 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 406 | blk.33.ffn_down_exps.weight | Block 33 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 407 | blk.33.ffn_gate_exps.weight | Block 33 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 408 | blk.33.ffn_gate_inp.weight | Block 33 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 409 | blk.33.ffn_norm.weight | Block 33 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 410 | blk.33.ffn_up_exps.weight | Block 33 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.33: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 34 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 411 | blk.34.attn_k.weight | Block 34 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 412 | blk.34.attn_k_norm.weight | Block 34 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 413 | blk.34.attn_norm.weight | Block 34 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 414 | blk.34.attn_output.weight | Block 34 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 415 | blk.34.attn_q.weight | Block 34 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 416 | blk.34.attn_q_norm.weight | Block 34 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 417 | blk.34.attn_v.weight | Block 34 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 418 | blk.34.ffn_down_exps.weight | Block 34 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 419 | blk.34.ffn_gate_exps.weight | Block 34 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 420 | blk.34.ffn_gate_inp.weight | Block 34 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 421 | blk.34.ffn_norm.weight | Block 34 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 422 | blk.34.ffn_up_exps.weight | Block 34 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.34: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 35 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 423 | blk.35.attn_k.weight | Block 35 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q4_K |
+| 424 | blk.35.attn_k_norm.weight | Block 35 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 425 | blk.35.attn_norm.weight | Block 35 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 426 | blk.35.attn_output.weight | Block 35 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 427 | blk.35.attn_q.weight | Block 35 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q4_K |
+| 428 | blk.35.attn_q_norm.weight | Block 35 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 429 | blk.35.attn_v.weight | Block 35 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 430 | blk.35.ffn_down_exps.weight | Block 35 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 431 | blk.35.ffn_gate_exps.weight | Block 35 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+| 432 | blk.35.ffn_gate_inp.weight | Block 35 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 433 | blk.35.ffn_norm.weight | Block 35 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 434 | blk.35.ffn_up_exps.weight | Block 35 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q4_K |
+
+- Total elements in blk.35: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 36 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 435 | blk.36.attn_k.weight | Block 36 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 436 | blk.36.attn_k_norm.weight | Block 36 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 437 | blk.36.attn_norm.weight | Block 36 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 438 | blk.36.attn_output.weight | Block 36 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 439 | blk.36.attn_q.weight | Block 36 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q5_K |
+| 440 | blk.36.attn_q_norm.weight | Block 36 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 441 | blk.36.attn_v.weight | Block 36 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 442 | blk.36.ffn_down_exps.weight | Block 36 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 443 | blk.36.ffn_gate_exps.weight | Block 36 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+| 444 | blk.36.ffn_gate_inp.weight | Block 36 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 445 | blk.36.ffn_norm.weight | Block 36 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 446 | blk.36.ffn_up_exps.weight | Block 36 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+
+- Total elements in blk.36: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 37 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 447 | blk.37.attn_k.weight | Block 37 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 448 | blk.37.attn_k_norm.weight | Block 37 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 449 | blk.37.attn_norm.weight | Block 37 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 450 | blk.37.attn_output.weight | Block 37 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 451 | blk.37.attn_q.weight | Block 37 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q5_K |
+| 452 | blk.37.attn_q_norm.weight | Block 37 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 453 | blk.37.attn_v.weight | Block 37 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 454 | blk.37.ffn_down_exps.weight | Block 37 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 455 | blk.37.ffn_gate_exps.weight | Block 37 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+| 456 | blk.37.ffn_gate_inp.weight | Block 37 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 457 | blk.37.ffn_norm.weight | Block 37 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 458 | blk.37.ffn_up_exps.weight | Block 37 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+
+- Total elements in blk.37: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 38 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 459 | blk.38.attn_k.weight | Block 38 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 460 | blk.38.attn_k_norm.weight | Block 38 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 461 | blk.38.attn_norm.weight | Block 38 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 462 | blk.38.attn_output.weight | Block 38 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 463 | blk.38.attn_q.weight | Block 38 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q5_K |
+| 464 | blk.38.attn_q_norm.weight | Block 38 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 465 | blk.38.attn_v.weight | Block 38 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 466 | blk.38.ffn_down_exps.weight | Block 38 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 467 | blk.38.ffn_gate_exps.weight | Block 38 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+| 468 | blk.38.ffn_gate_inp.weight | Block 38 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 469 | blk.38.ffn_norm.weight | Block 38 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 470 | blk.38.ffn_up_exps.weight | Block 38 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+
+- Total elements in blk.38: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 39 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 471 | blk.39.attn_k.weight | Block 39 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 472 | blk.39.attn_k_norm.weight | Block 39 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 473 | blk.39.attn_norm.weight | Block 39 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 474 | blk.39.attn_output.weight | Block 39 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 475 | blk.39.attn_q.weight | Block 39 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q5_K |
+| 476 | blk.39.attn_q_norm.weight | Block 39 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 477 | blk.39.attn_v.weight | Block 39 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 478 | blk.39.ffn_down_exps.weight | Block 39 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 479 | blk.39.ffn_gate_exps.weight | Block 39 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+| 480 | blk.39.ffn_gate_inp.weight | Block 39 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 481 | blk.39.ffn_norm.weight | Block 39 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 482 | blk.39.ffn_up_exps.weight | Block 39 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+
+- Total elements in blk.39: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 40 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 483 | blk.40.attn_k.weight | Block 40 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 484 | blk.40.attn_k_norm.weight | Block 40 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 485 | blk.40.attn_norm.weight | Block 40 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 486 | blk.40.attn_output.weight | Block 40 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 487 | blk.40.attn_q.weight | Block 40 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q5_K |
+| 488 | blk.40.attn_q_norm.weight | Block 40 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 489 | blk.40.attn_v.weight | Block 40 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 490 | blk.40.ffn_down_exps.weight | Block 40 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 491 | blk.40.ffn_gate_exps.weight | Block 40 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+| 492 | blk.40.ffn_gate_inp.weight | Block 40 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 493 | blk.40.ffn_norm.weight | Block 40 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 494 | blk.40.ffn_up_exps.weight | Block 40 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+
+- Total elements in blk.40: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 41 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 495 | blk.41.attn_k.weight | Block 41 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 496 | blk.41.attn_k_norm.weight | Block 41 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 497 | blk.41.attn_norm.weight | Block 41 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 498 | blk.41.attn_output.weight | Block 41 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 499 | blk.41.attn_q.weight | Block 41 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q5_K |
+| 500 | blk.41.attn_q_norm.weight | Block 41 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 501 | blk.41.attn_v.weight | Block 41 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 502 | blk.41.ffn_down_exps.weight | Block 41 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 503 | blk.41.ffn_gate_exps.weight | Block 41 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+| 504 | blk.41.ffn_gate_inp.weight | Block 41 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 505 | blk.41.ffn_norm.weight | Block 41 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 506 | blk.41.ffn_up_exps.weight | Block 41 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+
+- Total elements in blk.41: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 42 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 507 | blk.42.attn_k.weight | Block 42 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 508 | blk.42.attn_k_norm.weight | Block 42 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 509 | blk.42.attn_norm.weight | Block 42 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 510 | blk.42.attn_output.weight | Block 42 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 511 | blk.42.attn_q.weight | Block 42 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q5_K |
+| 512 | blk.42.attn_q_norm.weight | Block 42 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 513 | blk.42.attn_v.weight | Block 42 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 514 | blk.42.ffn_down_exps.weight | Block 42 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 515 | blk.42.ffn_gate_exps.weight | Block 42 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+| 516 | blk.42.ffn_gate_inp.weight | Block 42 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 517 | blk.42.ffn_norm.weight | Block 42 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 518 | blk.42.ffn_up_exps.weight | Block 42 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+
+- Total elements in blk.42: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 43 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 519 | blk.43.attn_k.weight | Block 43 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 520 | blk.43.attn_k_norm.weight | Block 43 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 521 | blk.43.attn_norm.weight | Block 43 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 522 | blk.43.attn_output.weight | Block 43 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 523 | blk.43.attn_q.weight | Block 43 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q5_K |
+| 524 | blk.43.attn_q_norm.weight | Block 43 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 525 | blk.43.attn_v.weight | Block 43 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 526 | blk.43.ffn_down_exps.weight | Block 43 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 527 | blk.43.ffn_gate_exps.weight | Block 43 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+| 528 | blk.43.ffn_gate_inp.weight | Block 43 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 529 | blk.43.ffn_norm.weight | Block 43 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 530 | blk.43.ffn_up_exps.weight | Block 43 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+
+- Total elements in blk.43: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 44 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 531 | blk.44.attn_k.weight | Block 44 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 532 | blk.44.attn_k_norm.weight | Block 44 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 533 | blk.44.attn_norm.weight | Block 44 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 534 | blk.44.attn_output.weight | Block 44 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 535 | blk.44.attn_q.weight | Block 44 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q5_K |
+| 536 | blk.44.attn_q_norm.weight | Block 44 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 537 | blk.44.attn_v.weight | Block 44 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 538 | blk.44.ffn_down_exps.weight | Block 44 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 539 | blk.44.ffn_gate_exps.weight | Block 44 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+| 540 | blk.44.ffn_gate_inp.weight | Block 44 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 541 | blk.44.ffn_norm.weight | Block 44 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 542 | blk.44.ffn_up_exps.weight | Block 44 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+
+- Total elements in blk.44: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+### Block 45 Tensor Group : ~623M Elements
+
+| T_ID | Tensor Layer Name | Human Friendly Tensor Layer Name | Elements | Shape | Type |
+|-----:|:----------------------------|:-------------------------------------------------------------------------------------------|:------------------|:----------------------|:-----|
+| 543 | blk.45.attn_k.weight | Block 45 Attention Key (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q5_K |
+| 544 | blk.45.attn_k_norm.weight | Block 45 Attn_K_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 545 | blk.45.attn_norm.weight | Block 45 Attention Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 546 | blk.45.attn_output.weight | Block 45 Attention Output (W) | ( ~8M) 8388608 | 4096 x 2048 x 1 x 1 | Q5_K |
+| 547 | blk.45.attn_q.weight | Block 45 Attention Query (W) | ( ~8M) 8388608 | 2048 x 4096 x 1 x 1 | Q5_K |
+| 548 | blk.45.attn_q_norm.weight | Block 45 Attn_Q_Norm (W) | ( 128) 128 | 128 x 1 x 1 x 1 | F32 |
+| 549 | blk.45.attn_v.weight | Block 45 Attention Value (W) | ( ~1M) 1048576 | 2048 x 512 x 1 x 1 | Q6_K |
+| 550 | blk.45.ffn_down_exps.weight | Block 45 Ffn_Down_Exps (W) | (~201M) 201326592 | 768 x 2048 x 128 x 1 | Q6_K |
+| 551 | blk.45.ffn_gate_exps.weight | Block 45 Ffn_Gate_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+| 552 | blk.45.ffn_gate_inp.weight | Block 45 Expert-Routing Layer For The Feed-Forward Network In Mixture Of Expert Models (W) | (~262K) 262144 | 2048 x 128 x 1 x 1 | F32 |
+| 553 | blk.45.ffn_norm.weight | Block 45 Feed-Forward Network Normalization (W) | ( ~2K) 2048 | 2048 x 1 x 1 x 1 | F32 |
+| 554 | blk.45.ffn_up_exps.weight | Block 45 Ffn_Up_Exps (W) | (~201M) 201326592 | 2048 x 768 x 128 x 1 | Q5_K |
+
+- Total elements in blk.45: (~623M) 623120640
+- Percentage of total elements: 2.13%
+
+
+