Files
Dolphin-Mistral-24B-Venice-…/scores/Dolphin-Mistral-24B-Venice-Edition-Q4_K_M.md
2025-07-01 08:19:46 +01:00

98 KiB

Dolphin-Mistral-24B-Venice-Edition-pruned-Q4_K_M.gguf - GGUF Internal File Dump

  • Endian: LITTLE endian

Key Value Metadata Store

There are 46 key-value pairs in this file

POS TYPE Count Key Value
1 UINT32 1 GGUF.version 3
2 UINT64 1 GGUF.tensor_count 345
3 UINT64 1 GGUF.kv_count 43
4 STRING 1 general.architecture llama
5 STRING 1 general.type model
6 STRING 1 general.name Dolphin Mistral 24B Venice Edition
7 STRING 1 general.finetune Venice-Edition
8 STRING 1 general.basename Dolphin-Mistral
9 STRING 1 general.size_label 24B
10 STRING 1 general.license apache-2.0
11 UINT32 1 general.base_model.count 1
12 STRING 1 general.base_model.0.name Mistral Small 24B Instruct 2501
13 STRING 1 general.base_model.0.version 2501
14 STRING 1 general.base_model.0.organization Mistralai
15 STRING 1 general.base_model.0.repo_url https://huggingface.co/mistral...istral-Small-24B-Instruct-2501
16 UINT32 1 llama.context_length 32768
17 UINT32 1 llama.embedding_length 5120
18 UINT32 1 llama.feed_forward_length 32768
19 UINT32 1 llama.attention.head_count 32
20 UINT32 1 llama.attention.head_count_kv 8
21 FLOAT32 1 llama.rope.freq_base 100000000.0
22 FLOAT32 1 llama.attention.layer_norm_rms_epsilon 1e-05
23 UINT32 1 llama.attention.key_length 128
24 UINT32 1 llama.attention.value_length 128
25 UINT32 1 llama.vocab_size 131072
26 UINT32 1 llama.rope.dimension_count 128
27 STRING 1 tokenizer.ggml.model gpt2
28 STRING 1 tokenizer.ggml.pre tekken
29 [STRING] 131072 tokenizer.ggml.tokens [ <unk>, <s>, </s>, [INST], [/INST], ... ]
30 [INT32] 131072 tokenizer.ggml.token_type [ 3, 3, 3, 3, 3, 3, 3, ... ]
31 [STRING] 269443 tokenizer.ggml.merges [ Ġ Ġ, Ġ t, e r, i n, Ġ ĠĠĠ, ... ]
32 UINT32 1 tokenizer.ggml.bos_token_id 1
33 UINT32 1 tokenizer.ggml.eos_token_id 2
34 UINT32 1 tokenizer.ggml.unknown_token_id 0
35 UINT32 1 tokenizer.ggml.padding_token_id 11
36 BOOL 1 tokenizer.ggml.add_bos_token True
37 BOOL 1 tokenizer.ggml.add_eos_token False
38 STRING 1 tokenizer.chat_template {%- set today = strftime_now("... {%- endif %}{%- endfor %}
39 BOOL 1 tokenizer.ggml.add_space_prefix False
40 UINT32 1 general.quantization_version 2
41 UINT32 1 general.file_type 15
42 STRING 1 quantize.imatrix.file ./imatrix/imatrix-Dolphin-Mist...l-24B-Venice-Edition-small.dat
43 STRING 1 quantize.imatrix.dataset ../../datasets/imatrix/combined_eur_small.txt
44 UINT32 1 quantize.imatrix.entries_count 281
45 UINT32 1 quantize.imatrix.chunks_count 3192
46 UINT32 1 llama.block_count 38

Tensors Overview ~22B Elements

Total number of elements in all tensors: 22460892160 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 0x784500 0x16800000
1 output_norm.weight 0x16f84500 0x5000
2 token_embd.weight 0x16f89500 0x11300000
3 blk.0.attn_k.weight 0x28289500 0x226000
4 blk.0.attn_norm.weight 0x284af500 0x5000
5 blk.0.attn_output.weight 0x284b4500 0xb40000
6 blk.0.attn_q.weight 0x28ff4500 0x898000
7 blk.0.attn_v.weight 0x2988c500 0x2d0000
8 blk.0.ffn_down.weight 0x29b5c500 0x8340000
9 blk.0.ffn_gate.weight 0x31e9c500 0x44c0000
10 blk.0.ffn_norm.weight 0x3635c500 0x5000
11 blk.0.ffn_up.weight 0x36361500 0x44c0000
12 blk.1.attn_k.weight 0x3a821500 0x226000
13 blk.1.attn_norm.weight 0x3aa47500 0x5000
14 blk.1.attn_output.weight 0x3aa4c500 0xb40000
15 blk.1.attn_q.weight 0x3b58c500 0x898000
16 blk.1.attn_v.weight 0x3be24500 0x2d0000
17 blk.1.ffn_down.weight 0x3c0f4500 0x8340000
18 blk.1.ffn_gate.weight 0x44434500 0x44c0000
19 blk.1.ffn_norm.weight 0x488f4500 0x5000
20 blk.1.ffn_up.weight 0x488f9500 0x44c0000
21 blk.2.attn_k.weight 0x4cdb9500 0x226000
22 blk.2.attn_norm.weight 0x4cfdf500 0x5000
23 blk.2.attn_output.weight 0x4cfe4500 0xb40000
24 blk.2.attn_q.weight 0x4db24500 0x898000
25 blk.2.attn_v.weight 0x4e3bc500 0x2d0000
26 blk.2.ffn_down.weight 0x4e68c500 0x8340000
27 blk.2.ffn_gate.weight 0x569cc500 0x44c0000
28 blk.2.ffn_norm.weight 0x5ae8c500 0x5000
29 blk.2.ffn_up.weight 0x5ae91500 0x44c0000
30 blk.3.attn_k.weight 0x5f351500 0x226000
31 blk.3.attn_norm.weight 0x5f577500 0x5000
32 blk.3.attn_output.weight 0x5f57c500 0xb40000
33 blk.3.attn_q.weight 0x600bc500 0x898000
34 blk.3.attn_v.weight 0x60954500 0x2d0000
35 blk.3.ffn_down.weight 0x60c24500 0x8340000
36 blk.3.ffn_gate.weight 0x68f64500 0x44c0000
37 blk.3.ffn_norm.weight 0x6d424500 0x5000
38 blk.3.ffn_up.weight 0x6d429500 0x44c0000
39 blk.4.attn_k.weight 0x718e9500 0x226000
40 blk.4.attn_norm.weight 0x71b0f500 0x5000
41 blk.4.attn_output.weight 0x71b14500 0xb40000
42 blk.4.attn_q.weight 0x72654500 0x898000
43 blk.4.attn_v.weight 0x72eec500 0x370000
44 blk.4.ffn_down.weight 0x7325c500 0x8340000
45 blk.4.ffn_gate.weight 0x7b59c500 0x44c0000
46 blk.4.ffn_norm.weight 0x7fa5c500 0x5000
47 blk.4.ffn_up.weight 0x7fa61500 0x44c0000
48 blk.5.attn_k.weight 0x83f21500 0x226000
49 blk.5.attn_norm.weight 0x84147500 0x5000
50 blk.5.attn_output.weight 0x8414c500 0xb40000
51 blk.5.attn_q.weight 0x84c8c500 0x898000
52 blk.5.attn_v.weight 0x85524500 0x370000
53 blk.5.ffn_down.weight 0x85894500 0x5a00000
54 blk.5.ffn_gate.weight 0x8b294500 0x44c0000
55 blk.5.ffn_norm.weight 0x8f754500 0x5000
56 blk.5.ffn_up.weight 0x8f759500 0x44c0000
57 blk.6.attn_k.weight 0x93c19500 0x226000
58 blk.6.attn_norm.weight 0x93e3f500 0x5000
59 blk.6.attn_output.weight 0x93e44500 0xb40000
60 blk.6.attn_q.weight 0x94984500 0x898000
61 blk.6.attn_v.weight 0x9521c500 0x2d0000
62 blk.6.ffn_down.weight 0x954ec500 0x5a00000
63 blk.6.ffn_gate.weight 0x9aeec500 0x44c0000
64 blk.6.ffn_norm.weight 0x9f3ac500 0x5000
65 blk.6.ffn_up.weight 0x9f3b1500 0x44c0000
66 blk.7.attn_k.weight 0xa3871500 0x226000
67 blk.7.attn_norm.weight 0xa3a97500 0x5000
68 blk.7.attn_output.weight 0xa3a9c500 0xb40000
69 blk.7.attn_q.weight 0xa45dc500 0x898000
70 blk.7.attn_v.weight 0xa4e74500 0x370000
71 blk.7.ffn_down.weight 0xa51e4500 0x8340000
72 blk.7.ffn_gate.weight 0xad524500 0x44c0000
73 blk.7.ffn_norm.weight 0xb19e4500 0x5000
74 blk.7.ffn_up.weight 0xb19e9500 0x44c0000
75 blk.8.attn_k.weight 0xb5ea9500 0x226000
76 blk.8.attn_norm.weight 0xb60cf500 0x5000
77 blk.8.attn_output.weight 0xb60d4500 0xb40000
78 blk.8.attn_q.weight 0xb6c14500 0x898000
79 blk.8.attn_v.weight 0xb74ac500 0x370000
80 blk.8.ffn_down.weight 0xb781c500 0x5a00000
81 blk.8.ffn_gate.weight 0xbd21c500 0x44c0000
82 blk.8.ffn_norm.weight 0xc16dc500 0x5000
83 blk.8.ffn_up.weight 0xc16e1500 0x44c0000
84 blk.9.attn_k.weight 0xc5ba1500 0x226000
85 blk.9.attn_norm.weight 0xc5dc7500 0x5000
86 blk.9.attn_output.weight 0xc5dcc500 0xb40000
87 blk.9.attn_q.weight 0xc690c500 0x898000
88 blk.9.attn_v.weight 0xc71a4500 0x2d0000
89 blk.9.ffn_down.weight 0xc7474500 0x5a00000
90 blk.9.ffn_gate.weight 0xcce74500 0x44c0000
91 blk.9.ffn_norm.weight 0xd1334500 0x5000
92 blk.9.ffn_up.weight 0xd1339500 0x44c0000
93 blk.10.attn_k.weight 0xd57f9500 0x226000
94 blk.10.attn_norm.weight 0xd5a1f500 0x5000
95 blk.10.attn_output.weight 0xd5a24500 0xb40000
96 blk.10.attn_q.weight 0xd6564500 0x898000
97 blk.10.attn_v.weight 0xd6dfc500 0x370000
98 blk.10.ffn_down.weight 0xd716c500 0x8340000
99 blk.10.ffn_gate.weight 0xdf4ac500 0x44c0000
100 blk.10.ffn_norm.weight 0xe396c500 0x5000
101 blk.10.ffn_up.weight 0xe3971500 0x44c0000
102 blk.11.attn_k.weight 0xe7e31500 0x226000
103 blk.11.attn_norm.weight 0xe8057500 0x5000
104 blk.11.attn_output.weight 0xe805c500 0xb40000
105 blk.11.attn_q.weight 0xe8b9c500 0x898000
106 blk.11.attn_v.weight 0xe9434500 0x370000
107 blk.11.ffn_down.weight 0xe97a4500 0x5a00000
108 blk.11.ffn_gate.weight 0xef1a4500 0x44c0000
109 blk.11.ffn_norm.weight 0xf3664500 0x5000
110 blk.11.ffn_up.weight 0xf3669500 0x44c0000
111 blk.12.attn_k.weight 0xf7b29500 0x226000
112 blk.12.attn_norm.weight 0xf7d4f500 0x5000
113 blk.12.attn_output.weight 0xf7d54500 0xb40000
114 blk.12.attn_q.weight 0xf8894500 0x898000
115 blk.12.attn_v.weight 0xf912c500 0x2d0000
116 blk.12.ffn_down.weight 0xf93fc500 0x5a00000
117 blk.12.ffn_gate.weight 0xfedfc500 0x44c0000
118 blk.12.ffn_norm.weight 0x1032bc500 0x5000
119 blk.12.ffn_up.weight 0x1032c1500 0x44c0000
120 blk.13.attn_k.weight 0x107781500 0x226000
121 blk.13.attn_norm.weight 0x1079a7500 0x5000
122 blk.13.attn_output.weight 0x1079ac500 0xb40000
123 blk.13.attn_q.weight 0x1084ec500 0x898000
124 blk.13.attn_v.weight 0x108d84500 0x370000
125 blk.13.ffn_down.weight 0x1090f4500 0x8340000
126 blk.13.ffn_gate.weight 0x111434500 0x44c0000
127 blk.13.ffn_norm.weight 0x1158f4500 0x5000
128 blk.13.ffn_up.weight 0x1158f9500 0x44c0000
129 blk.14.attn_k.weight 0x119db9500 0x226000
130 blk.14.attn_norm.weight 0x119fdf500 0x5000
131 blk.14.attn_output.weight 0x119fe4500 0xb40000
132 blk.14.attn_q.weight 0x11ab24500 0x898000
133 blk.14.attn_v.weight 0x11b3bc500 0x370000
134 blk.14.ffn_down.weight 0x11b72c500 0x5a00000
135 blk.14.ffn_gate.weight 0x12112c500 0x44c0000
136 blk.14.ffn_norm.weight 0x1255ec500 0x5000
137 blk.14.ffn_up.weight 0x1255f1500 0x44c0000
138 blk.15.attn_k.weight 0x129ab1500 0x226000
139 blk.15.attn_norm.weight 0x129cd7500 0x5000
140 blk.15.attn_output.weight 0x129cdc500 0xb40000
141 blk.15.attn_q.weight 0x12a81c500 0x898000
142 blk.15.attn_v.weight 0x12b0b4500 0x2d0000
143 blk.15.ffn_down.weight 0x12b384500 0x5a00000
144 blk.15.ffn_gate.weight 0x130d84500 0x44c0000
145 blk.15.ffn_norm.weight 0x135244500 0x5000
146 blk.15.ffn_up.weight 0x135249500 0x44c0000
147 blk.16.attn_k.weight 0x139709500 0x226000
148 blk.16.attn_norm.weight 0x13992f500 0x5000
149 blk.16.attn_output.weight 0x139934500 0xb40000
150 blk.16.attn_q.weight 0x13a474500 0x898000
151 blk.16.attn_v.weight 0x13ad0c500 0x370000
152 blk.16.ffn_down.weight 0x13b07c500 0x8340000
153 blk.16.ffn_gate.weight 0x1433bc500 0x44c0000
154 blk.16.ffn_norm.weight 0x14787c500 0x5000
155 blk.16.ffn_up.weight 0x147881500 0x44c0000
156 blk.17.attn_k.weight 0x14bd41500 0x2d0000
157 blk.17.attn_norm.weight 0x14c011500 0x5000
158 blk.17.attn_output.weight 0x14c016500 0xb40000
159 blk.17.attn_q.weight 0x14cb56500 0xb40000
160 blk.17.attn_v.weight 0x14d696500 0x370000
161 blk.17.ffn_down.weight 0x14da06500 0x5a00000
162 blk.17.ffn_gate.weight 0x153406500 0x44c0000
163 blk.17.ffn_norm.weight 0x1578c6500 0x5000
164 blk.17.ffn_up.weight 0x1578cb500 0x44c0000
165 blk.18.attn_k.weight 0x15bd8b500 0x2d0000
166 blk.18.attn_norm.weight 0x15c05b500 0x5000
167 blk.18.attn_output.weight 0x15c060500 0xb40000
168 blk.18.attn_q.weight 0x15cba0500 0xb40000
169 blk.18.attn_v.weight 0x15d6e0500 0x370000
170 blk.18.ffn_down.weight 0x15da50500 0x5a00000
171 blk.18.ffn_gate.weight 0x163450500 0x44c0000
172 blk.18.ffn_norm.weight 0x167910500 0x5000
173 blk.18.ffn_up.weight 0x167915500 0x44c0000
174 blk.19.attn_k.weight 0x16bdd5500 0x226000
175 blk.19.attn_norm.weight 0x16bffb500 0x5000
176 blk.19.attn_output.weight 0x16c000500 0xb40000
177 blk.19.attn_q.weight 0x16cb40500 0x898000
178 blk.19.attn_v.weight 0x16d3d8500 0x370000
179 blk.19.ffn_down.weight 0x16d748500 0x8340000
180 blk.19.ffn_gate.weight 0x175a88500 0x44c0000
181 blk.19.ffn_norm.weight 0x179f48500 0x5000
182 blk.19.ffn_up.weight 0x179f4d500 0x44c0000
183 blk.20.attn_k.weight 0x17e40d500 0x2d0000
184 blk.20.attn_norm.weight 0x17e6dd500 0x5000
185 blk.20.attn_output.weight 0x17e6e2500 0xb40000
186 blk.20.attn_q.weight 0x17f222500 0xb40000
187 blk.20.attn_v.weight 0x17fd62500 0x370000
188 blk.20.ffn_down.weight 0x1800d2500 0x5a00000
189 blk.20.ffn_gate.weight 0x185ad2500 0x5a00000
190 blk.20.ffn_norm.weight 0x18b4d2500 0x5000
191 blk.20.ffn_up.weight 0x18b4d7500 0x5a00000
192 blk.21.attn_k.weight 0x190ed7500 0x226000
193 blk.21.attn_norm.weight 0x1910fd500 0x5000
194 blk.21.attn_output.weight 0x191102500 0xb40000
195 blk.21.attn_q.weight 0x191c42500 0x898000
196 blk.21.attn_v.weight 0x1924da500 0x2d0000
197 blk.21.ffn_down.weight 0x1927aa500 0x5a00000
198 blk.21.ffn_gate.weight 0x1981aa500 0x5a00000
199 blk.21.ffn_norm.weight 0x19dbaa500 0x5000
200 blk.21.ffn_up.weight 0x19dbaf500 0x5a00000
201 blk.22.attn_k.weight 0x1a35af500 0x2d0000
202 blk.22.attn_norm.weight 0x1a387f500 0x5000
203 blk.22.attn_output.weight 0x1a3884500 0xb40000
204 blk.22.attn_q.weight 0x1a43c4500 0xb40000
205 blk.22.attn_v.weight 0x1a4f04500 0x370000
206 blk.22.ffn_down.weight 0x1a5274500 0x8340000
207 blk.22.ffn_gate.weight 0x1ad5b4500 0x5a00000
208 blk.22.ffn_norm.weight 0x1b2fb4500 0x5000
209 blk.22.ffn_up.weight 0x1b2fb9500 0x5a00000
210 blk.23.attn_k.weight 0x1b89b9500 0x2d0000
211 blk.23.attn_norm.weight 0x1b8c89500 0x5000
212 blk.23.attn_output.weight 0x1b8c8e500 0xb40000
213 blk.23.attn_q.weight 0x1b97ce500 0xb40000
214 blk.23.attn_v.weight 0x1ba30e500 0x370000
215 blk.23.ffn_down.weight 0x1ba67e500 0x5a00000
216 blk.23.ffn_gate.weight 0x1c007e500 0x5a00000
217 blk.23.ffn_norm.weight 0x1c5a7e500 0x5000
218 blk.23.ffn_up.weight 0x1c5a83500 0x5a00000
219 blk.24.attn_k.weight 0x1cb483500 0x2d0000
220 blk.24.attn_norm.weight 0x1cb753500 0x5000
221 blk.24.attn_output.weight 0x1cb758500 0xb40000
222 blk.24.attn_q.weight 0x1cc298500 0xb40000
223 blk.24.attn_v.weight 0x1ccdd8500 0x370000
224 blk.24.ffn_down.weight 0x1cd148500 0x5a00000
225 blk.24.ffn_gate.weight 0x1d2b48500 0x5a00000
226 blk.24.ffn_norm.weight 0x1d8548500 0x5000
227 blk.24.ffn_up.weight 0x1d854d500 0x5a00000
228 blk.25.attn_k.weight 0x1ddf4d500 0x2d0000
229 blk.25.attn_norm.weight 0x1de21d500 0x5000
230 blk.25.attn_output.weight 0x1de222500 0xb40000
231 blk.25.attn_q.weight 0x1ded62500 0xb40000
232 blk.25.attn_v.weight 0x1df8a2500 0x370000
233 blk.25.ffn_down.weight 0x1dfc12500 0x8340000
234 blk.25.ffn_gate.weight 0x1e7f52500 0x5a00000
235 blk.25.ffn_norm.weight 0x1ed952500 0x5000
236 blk.25.ffn_up.weight 0x1ed957500 0x5a00000
237 blk.26.attn_k.weight 0x1f3357500 0x2d0000
238 blk.26.attn_norm.weight 0x1f3627500 0x5000
239 blk.26.attn_output.weight 0x1f362c500 0xb40000
240 blk.26.attn_q.weight 0x1f416c500 0xb40000
241 blk.26.attn_v.weight 0x1f4cac500 0x370000
242 blk.26.ffn_down.weight 0x1f501c500 0x5a00000
243 blk.26.ffn_gate.weight 0x1faa1c500 0x5a00000
244 blk.26.ffn_norm.weight 0x20041c500 0x5000
245 blk.26.ffn_up.weight 0x200421500 0x5a00000
246 blk.27.attn_k.weight 0x205e21500 0x226000
247 blk.27.attn_norm.weight 0x206047500 0x5000
248 blk.27.attn_output.weight 0x20604c500 0xb40000
249 blk.27.attn_q.weight 0x206b8c500 0x898000
250 blk.27.attn_v.weight 0x207424500 0x2d0000
251 blk.27.ffn_down.weight 0x2076f4500 0x5a00000
252 blk.27.ffn_gate.weight 0x20d0f4500 0x5a00000
253 blk.27.ffn_norm.weight 0x212af4500 0x5000
254 blk.27.ffn_up.weight 0x212af9500 0x5a00000
255 blk.28.attn_k.weight 0x2184f9500 0x2d0000
256 blk.28.attn_norm.weight 0x2187c9500 0x5000
257 blk.28.attn_output.weight 0x2187ce500 0xb40000
258 blk.28.attn_q.weight 0x21930e500 0xb40000
259 blk.28.attn_v.weight 0x219e4e500 0x370000
260 blk.28.ffn_down.weight 0x21a1be500 0x8340000
261 blk.28.ffn_gate.weight 0x2224fe500 0x5a00000
262 blk.28.ffn_norm.weight 0x227efe500 0x5000
263 blk.28.ffn_up.weight 0x227f03500 0x5a00000
264 blk.29.attn_k.weight 0x22d903500 0x2d0000
265 blk.29.attn_norm.weight 0x22dbd3500 0x5000
266 blk.29.attn_output.weight 0x22dbd8500 0xb40000
267 blk.29.attn_q.weight 0x22e718500 0xb40000
268 blk.29.attn_v.weight 0x22f258500 0x370000
269 blk.29.ffn_down.weight 0x22f5c8500 0x5a00000
270 blk.29.ffn_gate.weight 0x234fc8500 0x5a00000
271 blk.29.ffn_norm.weight 0x23a9c8500 0x5000
272 blk.29.ffn_up.weight 0x23a9cd500 0x5a00000
273 blk.30.attn_k.weight 0x2403cd500 0x2d0000
274 blk.30.attn_norm.weight 0x24069d500 0x5000
275 blk.30.attn_output.weight 0x2406a2500 0xb40000
276 blk.30.attn_q.weight 0x2411e2500 0xb40000
277 blk.30.attn_v.weight 0x241d22500 0x370000
278 blk.30.ffn_down.weight 0x242092500 0x5a00000
279 blk.30.ffn_gate.weight 0x247a92500 0x5a00000
280 blk.30.ffn_norm.weight 0x24d492500 0x5000
281 blk.30.ffn_up.weight 0x24d497500 0x5a00000
282 blk.31.attn_k.weight 0x252e97500 0x2d0000
283 blk.31.attn_norm.weight 0x253167500 0x5000
284 blk.31.attn_output.weight 0x25316c500 0xb40000
285 blk.31.attn_q.weight 0x253cac500 0xb40000
286 blk.31.attn_v.weight 0x2547ec500 0x370000
287 blk.31.ffn_down.weight 0x254b5c500 0x8340000
288 blk.31.ffn_gate.weight 0x25ce9c500 0x5a00000
289 blk.31.ffn_norm.weight 0x26289c500 0x5000
290 blk.31.ffn_up.weight 0x2628a1500 0x5a00000
291 blk.32.attn_k.weight 0x2682a1500 0x2d0000
292 blk.32.attn_norm.weight 0x268571500 0x5000
293 blk.32.attn_output.weight 0x268576500 0xb40000
294 blk.32.attn_q.weight 0x2690b6500 0xb40000
295 blk.32.attn_v.weight 0x269bf6500 0x370000
296 blk.32.ffn_down.weight 0x269f66500 0x5a00000
297 blk.32.ffn_gate.weight 0x26f966500 0x5a00000
298 blk.32.ffn_norm.weight 0x275366500 0x5000
299 blk.32.ffn_up.weight 0x27536b500 0x5a00000
300 blk.33.attn_k.weight 0x27ad6b500 0x2d0000
301 blk.33.attn_norm.weight 0x27b03b500 0x5000
302 blk.33.attn_output.weight 0x27b040500 0xb40000
303 blk.33.attn_q.weight 0x27bb80500 0xb40000
304 blk.33.attn_v.weight 0x27c6c0500 0x370000
305 blk.33.ffn_down.weight 0x27ca30500 0x5a00000
306 blk.33.ffn_gate.weight 0x282430500 0x5a00000
307 blk.33.ffn_norm.weight 0x287e30500 0x5000
308 blk.33.ffn_up.weight 0x287e35500 0x5a00000
309 blk.34.attn_k.weight 0x28d835500 0x2d0000
310 blk.34.attn_norm.weight 0x28db05500 0x5000
311 blk.34.attn_output.weight 0x28db0a500 0xb40000
312 blk.34.attn_q.weight 0x28e64a500 0xb40000
313 blk.34.attn_v.weight 0x28f18a500 0x370000
314 blk.34.ffn_down.weight 0x28f4fa500 0x8340000
315 blk.34.ffn_gate.weight 0x29783a500 0x5a00000
316 blk.34.ffn_norm.weight 0x29d23a500 0x5000
317 blk.34.ffn_up.weight 0x29d23f500 0x5a00000
318 blk.35.attn_k.weight 0x2a2c3f500 0x2d0000
319 blk.35.attn_norm.weight 0x2a2f0f500 0x5000
320 blk.35.attn_output.weight 0x2a2f14500 0xb40000
321 blk.35.attn_q.weight 0x2a3a54500 0xb40000
322 blk.35.attn_v.weight 0x2a4594500 0x370000
323 blk.35.ffn_down.weight 0x2a4904500 0x8340000
324 blk.35.ffn_gate.weight 0x2acc44500 0x5a00000
325 blk.35.ffn_norm.weight 0x2b2644500 0x5000
326 blk.35.ffn_up.weight 0x2b2649500 0x5a00000
327 blk.36.attn_k.weight 0x2b8049500 0x2d0000
328 blk.36.attn_norm.weight 0x2b8319500 0x5000
329 blk.36.attn_output.weight 0x2b831e500 0xb40000
330 blk.36.attn_q.weight 0x2b8e5e500 0xb40000
331 blk.36.attn_v.weight 0x2b999e500 0x370000
332 blk.36.ffn_down.weight 0x2b9d0e500 0x8340000
333 blk.36.ffn_gate.weight 0x2c204e500 0x5a00000
334 blk.36.ffn_norm.weight 0x2c7a4e500 0x5000
335 blk.36.ffn_up.weight 0x2c7a53500 0x5a00000
336 blk.37.attn_k.weight 0x2cd453500 0x2d0000
337 blk.37.attn_norm.weight 0x2cd723500 0x5000
338 blk.37.attn_output.weight 0x2cd728500 0xb40000
339 blk.37.attn_q.weight 0x2ce268500 0xb40000
340 blk.37.attn_v.weight 0x2ceda8500 0x370000
341 blk.37.ffn_down.weight 0x2cf118500 0x8340000
342 blk.37.ffn_gate.weight 0x2d7458500 0x5a00000
343 blk.37.ffn_norm.weight 0x2dce58500 0x5000
344 blk.37.ffn_up.weight 0x2dce5d500 0x5a00000

Base Tensor Group : ~1B Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
0 output.weight Output (W) (~671M) 671088640 5120 x 131072 x 1 x 1 Q4_K
1 output_norm.weight Output Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
2 token_embd.weight Token Embedding (W) (~671M) 671088640 5120 x 131072 x 1 x 1 Q3_K
  • Total elements in base: ( ~1B) 1342182400
  • Percentage of total elements: 5.98%

Block 0 Tensor Group : ~556M 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) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
4 blk.0.attn_norm.weight Block 0 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
5 blk.0.attn_output.weight Block 0 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
6 blk.0.attn_q.weight Block 0 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
7 blk.0.attn_v.weight Block 0 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
8 blk.0.ffn_down.weight Block 0 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
9 blk.0.ffn_gate.weight Block 0 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
10 blk.0.ffn_norm.weight Block 0 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
11 blk.0.ffn_up.weight Block 0 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.0: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 1 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
12 blk.1.attn_k.weight Block 1 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
13 blk.1.attn_norm.weight Block 1 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
14 blk.1.attn_output.weight Block 1 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
15 blk.1.attn_q.weight Block 1 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
16 blk.1.attn_v.weight Block 1 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
17 blk.1.ffn_down.weight Block 1 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
18 blk.1.ffn_gate.weight Block 1 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
19 blk.1.ffn_norm.weight Block 1 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
20 blk.1.ffn_up.weight Block 1 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.1: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 2 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
21 blk.2.attn_k.weight Block 2 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
22 blk.2.attn_norm.weight Block 2 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
23 blk.2.attn_output.weight Block 2 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
24 blk.2.attn_q.weight Block 2 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
25 blk.2.attn_v.weight Block 2 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
26 blk.2.ffn_down.weight Block 2 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
27 blk.2.ffn_gate.weight Block 2 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
28 blk.2.ffn_norm.weight Block 2 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
29 blk.2.ffn_up.weight Block 2 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.2: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 3 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
30 blk.3.attn_k.weight Block 3 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
31 blk.3.attn_norm.weight Block 3 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
32 blk.3.attn_output.weight Block 3 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
33 blk.3.attn_q.weight Block 3 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
34 blk.3.attn_v.weight Block 3 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
35 blk.3.ffn_down.weight Block 3 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
36 blk.3.ffn_gate.weight Block 3 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
37 blk.3.ffn_norm.weight Block 3 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
38 blk.3.ffn_up.weight Block 3 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.3: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 4 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
39 blk.4.attn_k.weight Block 4 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
40 blk.4.attn_norm.weight Block 4 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
41 blk.4.attn_output.weight Block 4 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
42 blk.4.attn_q.weight Block 4 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
43 blk.4.attn_v.weight Block 4 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
44 blk.4.ffn_down.weight Block 4 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
45 blk.4.ffn_gate.weight Block 4 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
46 blk.4.ffn_norm.weight Block 4 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
47 blk.4.ffn_up.weight Block 4 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.4: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 5 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
48 blk.5.attn_k.weight Block 5 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
49 blk.5.attn_norm.weight Block 5 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
50 blk.5.attn_output.weight Block 5 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
51 blk.5.attn_q.weight Block 5 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
52 blk.5.attn_v.weight Block 5 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
53 blk.5.ffn_down.weight Block 5 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
54 blk.5.ffn_gate.weight Block 5 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
55 blk.5.ffn_norm.weight Block 5 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
56 blk.5.ffn_up.weight Block 5 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.5: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 6 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
57 blk.6.attn_k.weight Block 6 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
58 blk.6.attn_norm.weight Block 6 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
59 blk.6.attn_output.weight Block 6 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
60 blk.6.attn_q.weight Block 6 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
61 blk.6.attn_v.weight Block 6 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
62 blk.6.ffn_down.weight Block 6 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
63 blk.6.ffn_gate.weight Block 6 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
64 blk.6.ffn_norm.weight Block 6 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
65 blk.6.ffn_up.weight Block 6 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.6: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 7 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
66 blk.7.attn_k.weight Block 7 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
67 blk.7.attn_norm.weight Block 7 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
68 blk.7.attn_output.weight Block 7 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
69 blk.7.attn_q.weight Block 7 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
70 blk.7.attn_v.weight Block 7 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
71 blk.7.ffn_down.weight Block 7 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
72 blk.7.ffn_gate.weight Block 7 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
73 blk.7.ffn_norm.weight Block 7 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
74 blk.7.ffn_up.weight Block 7 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.7: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 8 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
75 blk.8.attn_k.weight Block 8 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
76 blk.8.attn_norm.weight Block 8 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
77 blk.8.attn_output.weight Block 8 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
78 blk.8.attn_q.weight Block 8 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
79 blk.8.attn_v.weight Block 8 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
80 blk.8.ffn_down.weight Block 8 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
81 blk.8.ffn_gate.weight Block 8 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
82 blk.8.ffn_norm.weight Block 8 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
83 blk.8.ffn_up.weight Block 8 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.8: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 9 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
84 blk.9.attn_k.weight Block 9 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
85 blk.9.attn_norm.weight Block 9 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
86 blk.9.attn_output.weight Block 9 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
87 blk.9.attn_q.weight Block 9 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
88 blk.9.attn_v.weight Block 9 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
89 blk.9.ffn_down.weight Block 9 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
90 blk.9.ffn_gate.weight Block 9 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
91 blk.9.ffn_norm.weight Block 9 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
92 blk.9.ffn_up.weight Block 9 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.9: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 10 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
93 blk.10.attn_k.weight Block 10 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
94 blk.10.attn_norm.weight Block 10 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
95 blk.10.attn_output.weight Block 10 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
96 blk.10.attn_q.weight Block 10 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
97 blk.10.attn_v.weight Block 10 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
98 blk.10.ffn_down.weight Block 10 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
99 blk.10.ffn_gate.weight Block 10 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
100 blk.10.ffn_norm.weight Block 10 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
101 blk.10.ffn_up.weight Block 10 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.10: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 11 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
102 blk.11.attn_k.weight Block 11 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
103 blk.11.attn_norm.weight Block 11 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
104 blk.11.attn_output.weight Block 11 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
105 blk.11.attn_q.weight Block 11 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
106 blk.11.attn_v.weight Block 11 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
107 blk.11.ffn_down.weight Block 11 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
108 blk.11.ffn_gate.weight Block 11 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
109 blk.11.ffn_norm.weight Block 11 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
110 blk.11.ffn_up.weight Block 11 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.11: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 12 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
111 blk.12.attn_k.weight Block 12 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
112 blk.12.attn_norm.weight Block 12 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
113 blk.12.attn_output.weight Block 12 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
114 blk.12.attn_q.weight Block 12 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
115 blk.12.attn_v.weight Block 12 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
116 blk.12.ffn_down.weight Block 12 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
117 blk.12.ffn_gate.weight Block 12 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
118 blk.12.ffn_norm.weight Block 12 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
119 blk.12.ffn_up.weight Block 12 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.12: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 13 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
120 blk.13.attn_k.weight Block 13 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
121 blk.13.attn_norm.weight Block 13 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
122 blk.13.attn_output.weight Block 13 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
123 blk.13.attn_q.weight Block 13 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
124 blk.13.attn_v.weight Block 13 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
125 blk.13.ffn_down.weight Block 13 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
126 blk.13.ffn_gate.weight Block 13 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
127 blk.13.ffn_norm.weight Block 13 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
128 blk.13.ffn_up.weight Block 13 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.13: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 14 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
129 blk.14.attn_k.weight Block 14 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
130 blk.14.attn_norm.weight Block 14 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
131 blk.14.attn_output.weight Block 14 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
132 blk.14.attn_q.weight Block 14 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
133 blk.14.attn_v.weight Block 14 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
134 blk.14.ffn_down.weight Block 14 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
135 blk.14.ffn_gate.weight Block 14 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
136 blk.14.ffn_norm.weight Block 14 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
137 blk.14.ffn_up.weight Block 14 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.14: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 15 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
138 blk.15.attn_k.weight Block 15 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
139 blk.15.attn_norm.weight Block 15 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
140 blk.15.attn_output.weight Block 15 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
141 blk.15.attn_q.weight Block 15 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
142 blk.15.attn_v.weight Block 15 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
143 blk.15.ffn_down.weight Block 15 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
144 blk.15.ffn_gate.weight Block 15 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
145 blk.15.ffn_norm.weight Block 15 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
146 blk.15.ffn_up.weight Block 15 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.15: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 16 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
147 blk.16.attn_k.weight Block 16 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
148 blk.16.attn_norm.weight Block 16 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
149 blk.16.attn_output.weight Block 16 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
150 blk.16.attn_q.weight Block 16 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
151 blk.16.attn_v.weight Block 16 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
152 blk.16.ffn_down.weight Block 16 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
153 blk.16.ffn_gate.weight Block 16 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
154 blk.16.ffn_norm.weight Block 16 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
155 blk.16.ffn_up.weight Block 16 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.16: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 17 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
156 blk.17.attn_k.weight Block 17 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
157 blk.17.attn_norm.weight Block 17 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
158 blk.17.attn_output.weight Block 17 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
159 blk.17.attn_q.weight Block 17 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
160 blk.17.attn_v.weight Block 17 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
161 blk.17.ffn_down.weight Block 17 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
162 blk.17.ffn_gate.weight Block 17 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
163 blk.17.ffn_norm.weight Block 17 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
164 blk.17.ffn_up.weight Block 17 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.17: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 18 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
165 blk.18.attn_k.weight Block 18 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
166 blk.18.attn_norm.weight Block 18 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
167 blk.18.attn_output.weight Block 18 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
168 blk.18.attn_q.weight Block 18 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
169 blk.18.attn_v.weight Block 18 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
170 blk.18.ffn_down.weight Block 18 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
171 blk.18.ffn_gate.weight Block 18 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
172 blk.18.ffn_norm.weight Block 18 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
173 blk.18.ffn_up.weight Block 18 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.18: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 19 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
174 blk.19.attn_k.weight Block 19 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
175 blk.19.attn_norm.weight Block 19 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
176 blk.19.attn_output.weight Block 19 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
177 blk.19.attn_q.weight Block 19 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
178 blk.19.attn_v.weight Block 19 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
179 blk.19.ffn_down.weight Block 19 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
180 blk.19.ffn_gate.weight Block 19 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
181 blk.19.ffn_norm.weight Block 19 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
182 blk.19.ffn_up.weight Block 19 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q3_K
  • Total elements in blk.19: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 20 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
183 blk.20.attn_k.weight Block 20 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
184 blk.20.attn_norm.weight Block 20 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
185 blk.20.attn_output.weight Block 20 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
186 blk.20.attn_q.weight Block 20 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
187 blk.20.attn_v.weight Block 20 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
188 blk.20.ffn_down.weight Block 20 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
189 blk.20.ffn_gate.weight Block 20 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
190 blk.20.ffn_norm.weight Block 20 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
191 blk.20.ffn_up.weight Block 20 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.20: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 21 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
192 blk.21.attn_k.weight Block 21 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
193 blk.21.attn_norm.weight Block 21 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
194 blk.21.attn_output.weight Block 21 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
195 blk.21.attn_q.weight Block 21 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
196 blk.21.attn_v.weight Block 21 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
197 blk.21.ffn_down.weight Block 21 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
198 blk.21.ffn_gate.weight Block 21 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
199 blk.21.ffn_norm.weight Block 21 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
200 blk.21.ffn_up.weight Block 21 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.21: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 22 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
201 blk.22.attn_k.weight Block 22 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
202 blk.22.attn_norm.weight Block 22 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
203 blk.22.attn_output.weight Block 22 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
204 blk.22.attn_q.weight Block 22 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
205 blk.22.attn_v.weight Block 22 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
206 blk.22.ffn_down.weight Block 22 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
207 blk.22.ffn_gate.weight Block 22 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
208 blk.22.ffn_norm.weight Block 22 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
209 blk.22.ffn_up.weight Block 22 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.22: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 23 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
210 blk.23.attn_k.weight Block 23 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
211 blk.23.attn_norm.weight Block 23 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
212 blk.23.attn_output.weight Block 23 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
213 blk.23.attn_q.weight Block 23 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
214 blk.23.attn_v.weight Block 23 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
215 blk.23.ffn_down.weight Block 23 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
216 blk.23.ffn_gate.weight Block 23 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
217 blk.23.ffn_norm.weight Block 23 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
218 blk.23.ffn_up.weight Block 23 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.23: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 24 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
219 blk.24.attn_k.weight Block 24 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
220 blk.24.attn_norm.weight Block 24 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
221 blk.24.attn_output.weight Block 24 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
222 blk.24.attn_q.weight Block 24 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
223 blk.24.attn_v.weight Block 24 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
224 blk.24.ffn_down.weight Block 24 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
225 blk.24.ffn_gate.weight Block 24 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
226 blk.24.ffn_norm.weight Block 24 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
227 blk.24.ffn_up.weight Block 24 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.24: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 25 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
228 blk.25.attn_k.weight Block 25 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
229 blk.25.attn_norm.weight Block 25 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
230 blk.25.attn_output.weight Block 25 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
231 blk.25.attn_q.weight Block 25 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
232 blk.25.attn_v.weight Block 25 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
233 blk.25.ffn_down.weight Block 25 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
234 blk.25.ffn_gate.weight Block 25 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
235 blk.25.ffn_norm.weight Block 25 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
236 blk.25.ffn_up.weight Block 25 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.25: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 26 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
237 blk.26.attn_k.weight Block 26 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
238 blk.26.attn_norm.weight Block 26 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
239 blk.26.attn_output.weight Block 26 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
240 blk.26.attn_q.weight Block 26 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
241 blk.26.attn_v.weight Block 26 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
242 blk.26.ffn_down.weight Block 26 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
243 blk.26.ffn_gate.weight Block 26 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
244 blk.26.ffn_norm.weight Block 26 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
245 blk.26.ffn_up.weight Block 26 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.26: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 27 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
246 blk.27.attn_k.weight Block 27 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q3_K
247 blk.27.attn_norm.weight Block 27 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
248 blk.27.attn_output.weight Block 27 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
249 blk.27.attn_q.weight Block 27 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q3_K
250 blk.27.attn_v.weight Block 27 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
251 blk.27.ffn_down.weight Block 27 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
252 blk.27.ffn_gate.weight Block 27 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
253 blk.27.ffn_norm.weight Block 27 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
254 blk.27.ffn_up.weight Block 27 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.27: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 28 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
255 blk.28.attn_k.weight Block 28 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
256 blk.28.attn_norm.weight Block 28 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
257 blk.28.attn_output.weight Block 28 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
258 blk.28.attn_q.weight Block 28 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
259 blk.28.attn_v.weight Block 28 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
260 blk.28.ffn_down.weight Block 28 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
261 blk.28.ffn_gate.weight Block 28 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
262 blk.28.ffn_norm.weight Block 28 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
263 blk.28.ffn_up.weight Block 28 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.28: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 29 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
264 blk.29.attn_k.weight Block 29 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
265 blk.29.attn_norm.weight Block 29 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
266 blk.29.attn_output.weight Block 29 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
267 blk.29.attn_q.weight Block 29 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
268 blk.29.attn_v.weight Block 29 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
269 blk.29.ffn_down.weight Block 29 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
270 blk.29.ffn_gate.weight Block 29 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
271 blk.29.ffn_norm.weight Block 29 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
272 blk.29.ffn_up.weight Block 29 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.29: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 30 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
273 blk.30.attn_k.weight Block 30 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
274 blk.30.attn_norm.weight Block 30 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
275 blk.30.attn_output.weight Block 30 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
276 blk.30.attn_q.weight Block 30 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
277 blk.30.attn_v.weight Block 30 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
278 blk.30.ffn_down.weight Block 30 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
279 blk.30.ffn_gate.weight Block 30 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
280 blk.30.ffn_norm.weight Block 30 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
281 blk.30.ffn_up.weight Block 30 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.30: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 31 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
282 blk.31.attn_k.weight Block 31 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
283 blk.31.attn_norm.weight Block 31 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
284 blk.31.attn_output.weight Block 31 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
285 blk.31.attn_q.weight Block 31 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
286 blk.31.attn_v.weight Block 31 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
287 blk.31.ffn_down.weight Block 31 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
288 blk.31.ffn_gate.weight Block 31 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
289 blk.31.ffn_norm.weight Block 31 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
290 blk.31.ffn_up.weight Block 31 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.31: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 32 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
291 blk.32.attn_k.weight Block 32 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
292 blk.32.attn_norm.weight Block 32 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
293 blk.32.attn_output.weight Block 32 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
294 blk.32.attn_q.weight Block 32 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
295 blk.32.attn_v.weight Block 32 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
296 blk.32.ffn_down.weight Block 32 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
297 blk.32.ffn_gate.weight Block 32 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
298 blk.32.ffn_norm.weight Block 32 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
299 blk.32.ffn_up.weight Block 32 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.32: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 33 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
300 blk.33.attn_k.weight Block 33 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
301 blk.33.attn_norm.weight Block 33 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
302 blk.33.attn_output.weight Block 33 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
303 blk.33.attn_q.weight Block 33 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
304 blk.33.attn_v.weight Block 33 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
305 blk.33.ffn_down.weight Block 33 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q4_K
306 blk.33.ffn_gate.weight Block 33 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
307 blk.33.ffn_norm.weight Block 33 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
308 blk.33.ffn_up.weight Block 33 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.33: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 34 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
309 blk.34.attn_k.weight Block 34 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
310 blk.34.attn_norm.weight Block 34 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
311 blk.34.attn_output.weight Block 34 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
312 blk.34.attn_q.weight Block 34 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
313 blk.34.attn_v.weight Block 34 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
314 blk.34.ffn_down.weight Block 34 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
315 blk.34.ffn_gate.weight Block 34 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
316 blk.34.ffn_norm.weight Block 34 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
317 blk.34.ffn_up.weight Block 34 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.34: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 35 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
318 blk.35.attn_k.weight Block 35 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
319 blk.35.attn_norm.weight Block 35 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
320 blk.35.attn_output.weight Block 35 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
321 blk.35.attn_q.weight Block 35 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
322 blk.35.attn_v.weight Block 35 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
323 blk.35.ffn_down.weight Block 35 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
324 blk.35.ffn_gate.weight Block 35 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
325 blk.35.ffn_norm.weight Block 35 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
326 blk.35.ffn_up.weight Block 35 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.35: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 36 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
327 blk.36.attn_k.weight Block 36 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
328 blk.36.attn_norm.weight Block 36 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
329 blk.36.attn_output.weight Block 36 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
330 blk.36.attn_q.weight Block 36 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
331 blk.36.attn_v.weight Block 36 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
332 blk.36.ffn_down.weight Block 36 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
333 blk.36.ffn_gate.weight Block 36 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
334 blk.36.ffn_norm.weight Block 36 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
335 blk.36.ffn_up.weight Block 36 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.36: (~556M) 555755520
  • Percentage of total elements: 2.47%

Block 37 Tensor Group : ~556M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
336 blk.37.attn_k.weight Block 37 Attention Key (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q4_K
337 blk.37.attn_norm.weight Block 37 Attention Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
338 blk.37.attn_output.weight Block 37 Attention Output (W) ( ~21M) 20971520 4096 x 5120 x 1 x 1 Q4_K
339 blk.37.attn_q.weight Block 37 Attention Query (W) ( ~21M) 20971520 5120 x 4096 x 1 x 1 Q4_K
340 blk.37.attn_v.weight Block 37 Attention Value (W) ( ~5M) 5242880 5120 x 1024 x 1 x 1 Q5_K
341 blk.37.ffn_down.weight Block 37 Feed-Forward Network "Down" (W) (~168M) 167772160 32768 x 5120 x 1 x 1 Q6_K
342 blk.37.ffn_gate.weight Block 37 Feed-Forward Network "Gate" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
343 blk.37.ffn_norm.weight Block 37 Feed-Forward Network Normalization (W) ( ~5K) 5120 5120 x 1 x 1 x 1 F32
344 blk.37.ffn_up.weight Block 37 Feed-Forward Network "Up" (W) (~168M) 167772160 5120 x 32768 x 1 x 1 Q4_K
  • Total elements in blk.37: (~556M) 555755520
  • Percentage of total elements: 2.47%