DeepSeek-R1-Distill-Llama-8B-GGUF / scores /DeepSeek-R1-Distill-Llama-8B-Q3_K_L.md
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DeepSeek-R1-Distill-Llama-8B-Q3_K_L.gguf - GGUF Internal File Dump

  • Endian: LITTLE endian

Key Value Metadata Store

There are 36 key-value pairs in this file

POS TYPE Count Key Value
1 UINT32 1 GGUF.version 3
2 UINT64 1 GGUF.tensor_count 292
3 UINT64 1 GGUF.kv_count 33
4 STRING 1 general.architecture llama
5 STRING 1 general.type model
6 STRING 1 general.name DeepSeek R1 Distill Llama 8B
7 STRING 1 general.basename DeepSeek-R1-Distill-Llama
8 STRING 1 general.size_label 8B
9 STRING 1 general.license mit
10 UINT32 1 llama.block_count 32
11 UINT32 1 llama.context_length 131072
12 UINT32 1 llama.embedding_length 4096
13 UINT32 1 llama.feed_forward_length 14336
14 UINT32 1 llama.attention.head_count 32
15 UINT32 1 llama.attention.head_count_kv 8
16 FLOAT32 1 llama.rope.freq_base 500000.0
17 FLOAT32 1 llama.attention.layer_norm_rms_epsilon 1e-05
18 UINT32 1 llama.vocab_size 128256
19 UINT32 1 llama.rope.dimension_count 128
20 STRING 1 tokenizer.ggml.model gpt2
21 STRING 1 tokenizer.ggml.pre llama-bpe
22 [STRING] 128256 tokenizer.ggml.tokens [ !, ", #, $, %, ... ]
23 [INT32] 128256 tokenizer.ggml.token_type [ 1, 1, 1, 1, 1, 1, 1, ... ]
24 [STRING] 280147 tokenizer.ggml.merges [ Ġ Ġ, Ġ ĠĠĠ, ĠĠ ĠĠ, ĠĠĠ Ġ, i n, ... ]
25 UINT32 1 tokenizer.ggml.bos_token_id 128000
26 UINT32 1 tokenizer.ggml.eos_token_id 128001
27 UINT32 1 tokenizer.ggml.padding_token_id 128001
28 BOOL 1 tokenizer.ggml.add_bos_token True
29 BOOL 1 tokenizer.ggml.add_eos_token False
30 STRING 1 tokenizer.chat_template {% if not add_generation_promp...{{'<|Assistant|>'}}{% endif %}
31 UINT32 1 general.quantization_version 2
32 UINT32 1 general.file_type 13
33 STRING 1 quantize.imatrix.file ./imatrix/imatrix-DeepSeek-R1-Distill-Llama-8B-small.dat
34 STRING 1 quantize.imatrix.dataset ../../datasets/imatrix/calibration_all_small.txt
35 INT32 1 quantize.imatrix.entries_count 225
36 INT32 1 quantize.imatrix.chunks_count 1130

Tensors Overview ~8B Elements

Total number of elements in all tensors: 8030261312 Elements

Tensor Data Offset

This table contains the offset and data segment relative to start of file

T_ID Tensor Layer Name Data Offset (B) Data Size (B)
0 output.weight 0x779a80 0xd746000
1 output_norm.weight 0xdebfa80 0x4000
2 rope_freqs.weight 0xdec3a80 0x100
3 token_embd.weight 0xdec3b80 0xd746000
4 blk.0.attn_k.weight 0x1b609b80 0x1b8000
5 blk.0.attn_norm.weight 0x1b7c1b80 0x4000
6 blk.0.attn_output.weight 0x1b7c5b80 0xb00000
7 blk.0.attn_q.weight 0x1c2c5b80 0x6e0000
8 blk.0.attn_v.weight 0x1c9a5b80 0x240000
9 blk.0.ffn_down.weight 0x1cbe5b80 0x2680000
10 blk.0.ffn_gate.weight 0x1f265b80 0x1810000
11 blk.0.ffn_norm.weight 0x20a75b80 0x4000
12 blk.0.ffn_up.weight 0x20a79b80 0x1810000
13 blk.1.attn_k.weight 0x22289b80 0x1b8000
14 blk.1.attn_norm.weight 0x22441b80 0x4000
15 blk.1.attn_output.weight 0x22445b80 0xb00000
16 blk.1.attn_q.weight 0x22f45b80 0x6e0000
17 blk.1.attn_v.weight 0x23625b80 0x240000
18 blk.1.ffn_down.weight 0x23865b80 0x2680000
19 blk.1.ffn_gate.weight 0x25ee5b80 0x1810000
20 blk.1.ffn_norm.weight 0x276f5b80 0x4000
21 blk.1.ffn_up.weight 0x276f9b80 0x1810000
22 blk.2.attn_k.weight 0x28f09b80 0x1b8000
23 blk.2.attn_norm.weight 0x290c1b80 0x4000
24 blk.2.attn_output.weight 0x290c5b80 0xb00000
25 blk.2.attn_q.weight 0x29bc5b80 0x6e0000
26 blk.2.attn_v.weight 0x2a2a5b80 0x240000
27 blk.2.ffn_down.weight 0x2a4e5b80 0x2680000
28 blk.2.ffn_gate.weight 0x2cb65b80 0x1810000
29 blk.2.ffn_norm.weight 0x2e375b80 0x4000
30 blk.2.ffn_up.weight 0x2e379b80 0x1810000
31 blk.3.attn_k.weight 0x2fb89b80 0x1b8000
32 blk.3.attn_norm.weight 0x2fd41b80 0x4000
33 blk.3.attn_output.weight 0x2fd45b80 0xb00000
34 blk.3.attn_q.weight 0x30845b80 0x6e0000
35 blk.3.attn_v.weight 0x30f25b80 0x240000
36 blk.3.ffn_down.weight 0x31165b80 0x2680000
37 blk.3.ffn_gate.weight 0x337e5b80 0x1810000
38 blk.3.ffn_norm.weight 0x34ff5b80 0x4000
39 blk.3.ffn_up.weight 0x34ff9b80 0x1810000
40 blk.4.attn_k.weight 0x36809b80 0x1b8000
41 blk.4.attn_norm.weight 0x369c1b80 0x4000
42 blk.4.attn_output.weight 0x369c5b80 0xb00000
43 blk.4.attn_q.weight 0x374c5b80 0x6e0000
44 blk.4.attn_v.weight 0x37ba5b80 0x240000
45 blk.4.ffn_down.weight 0x37de5b80 0x2680000
46 blk.4.ffn_gate.weight 0x3a465b80 0x1810000
47 blk.4.ffn_norm.weight 0x3bc75b80 0x4000
48 blk.4.ffn_up.weight 0x3bc79b80 0x1810000
49 blk.5.attn_k.weight 0x3d489b80 0x1b8000
50 blk.5.attn_norm.weight 0x3d641b80 0x4000
51 blk.5.attn_output.weight 0x3d645b80 0xb00000
52 blk.5.attn_q.weight 0x3e145b80 0x6e0000
53 blk.5.attn_v.weight 0x3e825b80 0x240000
54 blk.5.ffn_down.weight 0x3ea65b80 0x2680000
55 blk.5.ffn_gate.weight 0x410e5b80 0x1810000
56 blk.5.ffn_norm.weight 0x428f5b80 0x4000
57 blk.5.ffn_up.weight 0x428f9b80 0x1810000
58 blk.6.attn_k.weight 0x44109b80 0x1b8000
59 blk.6.attn_norm.weight 0x442c1b80 0x4000
60 blk.6.attn_output.weight 0x442c5b80 0xb00000
61 blk.6.attn_q.weight 0x44dc5b80 0x6e0000
62 blk.6.attn_v.weight 0x454a5b80 0x240000
63 blk.6.ffn_down.weight 0x456e5b80 0x2680000
64 blk.6.ffn_gate.weight 0x47d65b80 0x1810000
65 blk.6.ffn_norm.weight 0x49575b80 0x4000
66 blk.6.ffn_up.weight 0x49579b80 0x1810000
67 blk.7.attn_k.weight 0x4ad89b80 0x1b8000
68 blk.7.attn_norm.weight 0x4af41b80 0x4000
69 blk.7.attn_output.weight 0x4af45b80 0xb00000
70 blk.7.attn_q.weight 0x4ba45b80 0x6e0000
71 blk.7.attn_v.weight 0x4c125b80 0x240000
72 blk.7.ffn_down.weight 0x4c365b80 0x2680000
73 blk.7.ffn_gate.weight 0x4e9e5b80 0x1810000
74 blk.7.ffn_norm.weight 0x501f5b80 0x4000
75 blk.7.ffn_up.weight 0x501f9b80 0x1810000
76 blk.8.attn_k.weight 0x51a09b80 0x1b8000
77 blk.8.attn_norm.weight 0x51bc1b80 0x4000
78 blk.8.attn_output.weight 0x51bc5b80 0xb00000
79 blk.8.attn_q.weight 0x526c5b80 0x6e0000
80 blk.8.attn_v.weight 0x52da5b80 0x240000
81 blk.8.ffn_down.weight 0x52fe5b80 0x2680000
82 blk.8.ffn_gate.weight 0x55665b80 0x1810000
83 blk.8.ffn_norm.weight 0x56e75b80 0x4000
84 blk.8.ffn_up.weight 0x56e79b80 0x1810000
85 blk.9.attn_k.weight 0x58689b80 0x1b8000
86 blk.9.attn_norm.weight 0x58841b80 0x4000
87 blk.9.attn_output.weight 0x58845b80 0xb00000
88 blk.9.attn_q.weight 0x59345b80 0x6e0000
89 blk.9.attn_v.weight 0x59a25b80 0x240000
90 blk.9.ffn_down.weight 0x59c65b80 0x2680000
91 blk.9.ffn_gate.weight 0x5c2e5b80 0x1810000
92 blk.9.ffn_norm.weight 0x5daf5b80 0x4000
93 blk.9.ffn_up.weight 0x5daf9b80 0x1810000
94 blk.10.attn_k.weight 0x5f309b80 0x1b8000
95 blk.10.attn_norm.weight 0x5f4c1b80 0x4000
96 blk.10.attn_output.weight 0x5f4c5b80 0xb00000
97 blk.10.attn_q.weight 0x5ffc5b80 0x6e0000
98 blk.10.attn_v.weight 0x606a5b80 0x240000
99 blk.10.ffn_down.weight 0x608e5b80 0x2680000
100 blk.10.ffn_gate.weight 0x62f65b80 0x1810000
101 blk.10.ffn_norm.weight 0x64775b80 0x4000
102 blk.10.ffn_up.weight 0x64779b80 0x1810000
103 blk.11.attn_k.weight 0x65f89b80 0x1b8000
104 blk.11.attn_norm.weight 0x66141b80 0x4000
105 blk.11.attn_output.weight 0x66145b80 0xb00000
106 blk.11.attn_q.weight 0x66c45b80 0x6e0000
107 blk.11.attn_v.weight 0x67325b80 0x240000
108 blk.11.ffn_down.weight 0x67565b80 0x2680000
109 blk.11.ffn_gate.weight 0x69be5b80 0x1810000
110 blk.11.ffn_norm.weight 0x6b3f5b80 0x4000
111 blk.11.ffn_up.weight 0x6b3f9b80 0x1810000
112 blk.12.attn_k.weight 0x6cc09b80 0x1b8000
113 blk.12.attn_norm.weight 0x6cdc1b80 0x4000
114 blk.12.attn_output.weight 0x6cdc5b80 0xb00000
115 blk.12.attn_q.weight 0x6d8c5b80 0x6e0000
116 blk.12.attn_v.weight 0x6dfa5b80 0x240000
117 blk.12.ffn_down.weight 0x6e1e5b80 0x2680000
118 blk.12.ffn_gate.weight 0x70865b80 0x1810000
119 blk.12.ffn_norm.weight 0x72075b80 0x4000
120 blk.12.ffn_up.weight 0x72079b80 0x1810000
121 blk.13.attn_k.weight 0x73889b80 0x1b8000
122 blk.13.attn_norm.weight 0x73a41b80 0x4000
123 blk.13.attn_output.weight 0x73a45b80 0xb00000
124 blk.13.attn_q.weight 0x74545b80 0x6e0000
125 blk.13.attn_v.weight 0x74c25b80 0x240000
126 blk.13.ffn_down.weight 0x74e65b80 0x2680000
127 blk.13.ffn_gate.weight 0x774e5b80 0x1810000
128 blk.13.ffn_norm.weight 0x78cf5b80 0x4000
129 blk.13.ffn_up.weight 0x78cf9b80 0x1810000
130 blk.14.attn_k.weight 0x7a509b80 0x1b8000
131 blk.14.attn_norm.weight 0x7a6c1b80 0x4000
132 blk.14.attn_output.weight 0x7a6c5b80 0xb00000
133 blk.14.attn_q.weight 0x7b1c5b80 0x6e0000
134 blk.14.attn_v.weight 0x7b8a5b80 0x240000
135 blk.14.ffn_down.weight 0x7bae5b80 0x2680000
136 blk.14.ffn_gate.weight 0x7e165b80 0x1810000
137 blk.14.ffn_norm.weight 0x7f975b80 0x4000
138 blk.14.ffn_up.weight 0x7f979b80 0x1810000
139 blk.15.attn_k.weight 0x81189b80 0x1b8000
140 blk.15.attn_norm.weight 0x81341b80 0x4000
141 blk.15.attn_output.weight 0x81345b80 0xb00000
142 blk.15.attn_q.weight 0x81e45b80 0x6e0000
143 blk.15.attn_v.weight 0x82525b80 0x240000
144 blk.15.ffn_down.weight 0x82765b80 0x2680000
145 blk.15.ffn_gate.weight 0x84de5b80 0x1810000
146 blk.15.ffn_norm.weight 0x865f5b80 0x4000
147 blk.15.ffn_up.weight 0x865f9b80 0x1810000
148 blk.16.attn_k.weight 0x87e09b80 0x150000
149 blk.16.attn_norm.weight 0x87f59b80 0x4000
150 blk.16.attn_output.weight 0x87f5db80 0xb00000
151 blk.16.attn_q.weight 0x88a5db80 0x540000
152 blk.16.attn_v.weight 0x88f9db80 0x240000
153 blk.16.ffn_down.weight 0x891ddb80 0x1f80000
154 blk.16.ffn_gate.weight 0x8b15db80 0x1260000
155 blk.16.ffn_norm.weight 0x8c3bdb80 0x4000
156 blk.16.ffn_up.weight 0x8c3c1b80 0x1260000
157 blk.17.attn_k.weight 0x8d621b80 0x150000
158 blk.17.attn_norm.weight 0x8d771b80 0x4000
159 blk.17.attn_output.weight 0x8d775b80 0xb00000
160 blk.17.attn_q.weight 0x8e275b80 0x540000
161 blk.17.attn_v.weight 0x8e7b5b80 0x240000
162 blk.17.ffn_down.weight 0x8e9f5b80 0x1f80000
163 blk.17.ffn_gate.weight 0x90975b80 0x1260000
164 blk.17.ffn_norm.weight 0x91bd5b80 0x4000
165 blk.17.ffn_up.weight 0x91bd9b80 0x1260000
166 blk.18.attn_k.weight 0x92e39b80 0x150000
167 blk.18.attn_norm.weight 0x92f89b80 0x4000
168 blk.18.attn_output.weight 0x92f8db80 0xb00000
169 blk.18.attn_q.weight 0x93a8db80 0x540000
170 blk.18.attn_v.weight 0x93fcdb80 0x240000
171 blk.18.ffn_down.weight 0x9420db80 0x1f80000
172 blk.18.ffn_gate.weight 0x9618db80 0x1260000
173 blk.18.ffn_norm.weight 0x973edb80 0x4000
174 blk.18.ffn_up.weight 0x973f1b80 0x1260000
175 blk.19.attn_k.weight 0x98651b80 0x150000
176 blk.19.attn_norm.weight 0x987a1b80 0x4000
177 blk.19.attn_output.weight 0x987a5b80 0xb00000
178 blk.19.attn_q.weight 0x992a5b80 0x540000
179 blk.19.attn_v.weight 0x997e5b80 0x240000
180 blk.19.ffn_down.weight 0x99a25b80 0x1f80000
181 blk.19.ffn_gate.weight 0x9b9a5b80 0x1260000
182 blk.19.ffn_norm.weight 0x9cc05b80 0x4000
183 blk.19.ffn_up.weight 0x9cc09b80 0x1260000
184 blk.20.attn_k.weight 0x9de69b80 0x150000
185 blk.20.attn_norm.weight 0x9dfb9b80 0x4000
186 blk.20.attn_output.weight 0x9dfbdb80 0xb00000
187 blk.20.attn_q.weight 0x9eabdb80 0x540000
188 blk.20.attn_v.weight 0x9effdb80 0x240000
189 blk.20.ffn_down.weight 0x9f23db80 0x1f80000
190 blk.20.ffn_gate.weight 0xa11bdb80 0x1260000
191 blk.20.ffn_norm.weight 0xa241db80 0x4000
192 blk.20.ffn_up.weight 0xa2421b80 0x1260000
193 blk.21.attn_k.weight 0xa3681b80 0x150000
194 blk.21.attn_norm.weight 0xa37d1b80 0x4000
195 blk.21.attn_output.weight 0xa37d5b80 0xb00000
196 blk.21.attn_q.weight 0xa42d5b80 0x540000
197 blk.21.attn_v.weight 0xa4815b80 0x240000
198 blk.21.ffn_down.weight 0xa4a55b80 0x1f80000
199 blk.21.ffn_gate.weight 0xa69d5b80 0x1260000
200 blk.21.ffn_norm.weight 0xa7c35b80 0x4000
201 blk.21.ffn_up.weight 0xa7c39b80 0x1260000
202 blk.22.attn_k.weight 0xa8e99b80 0x150000
203 blk.22.attn_norm.weight 0xa8fe9b80 0x4000
204 blk.22.attn_output.weight 0xa8fedb80 0xb00000
205 blk.22.attn_q.weight 0xa9aedb80 0x540000
206 blk.22.attn_v.weight 0xaa02db80 0x240000
207 blk.22.ffn_down.weight 0xaa26db80 0x1f80000
208 blk.22.ffn_gate.weight 0xac1edb80 0x1260000
209 blk.22.ffn_norm.weight 0xad44db80 0x4000
210 blk.22.ffn_up.weight 0xad451b80 0x1260000
211 blk.23.attn_k.weight 0xae6b1b80 0x150000
212 blk.23.attn_norm.weight 0xae801b80 0x4000
213 blk.23.attn_output.weight 0xae805b80 0xb00000
214 blk.23.attn_q.weight 0xaf305b80 0x540000
215 blk.23.attn_v.weight 0xaf845b80 0x240000
216 blk.23.ffn_down.weight 0xafa85b80 0x1f80000
217 blk.23.ffn_gate.weight 0xb1a05b80 0x1260000
218 blk.23.ffn_norm.weight 0xb2c65b80 0x4000
219 blk.23.ffn_up.weight 0xb2c69b80 0x1260000
220 blk.24.attn_k.weight 0xb3ec9b80 0x150000
221 blk.24.attn_norm.weight 0xb4019b80 0x4000
222 blk.24.attn_output.weight 0xb401db80 0xb00000
223 blk.24.attn_q.weight 0xb4b1db80 0x540000
224 blk.24.attn_v.weight 0xb505db80 0x240000
225 blk.24.ffn_down.weight 0xb529db80 0x1f80000
226 blk.24.ffn_gate.weight 0xb721db80 0x1260000
227 blk.24.ffn_norm.weight 0xb847db80 0x4000
228 blk.24.ffn_up.weight 0xb8481b80 0x1260000
229 blk.25.attn_k.weight 0xb96e1b80 0x150000
230 blk.25.attn_norm.weight 0xb9831b80 0x4000
231 blk.25.attn_output.weight 0xb9835b80 0xb00000
232 blk.25.attn_q.weight 0xba335b80 0x540000
233 blk.25.attn_v.weight 0xba875b80 0x240000
234 blk.25.ffn_down.weight 0xbaab5b80 0x1f80000
235 blk.25.ffn_gate.weight 0xbca35b80 0x1260000
236 blk.25.ffn_norm.weight 0xbdc95b80 0x4000
237 blk.25.ffn_up.weight 0xbdc99b80 0x1260000
238 blk.26.attn_k.weight 0xbeef9b80 0x150000
239 blk.26.attn_norm.weight 0xbf049b80 0x4000
240 blk.26.attn_output.weight 0xbf04db80 0xb00000
241 blk.26.attn_q.weight 0xbfb4db80 0x540000
242 blk.26.attn_v.weight 0xc008db80 0x240000
243 blk.26.ffn_down.weight 0xc02cdb80 0x1f80000
244 blk.26.ffn_gate.weight 0xc224db80 0x1260000
245 blk.26.ffn_norm.weight 0xc34adb80 0x4000
246 blk.26.ffn_up.weight 0xc34b1b80 0x1260000
247 blk.27.attn_k.weight 0xc4711b80 0x150000
248 blk.27.attn_norm.weight 0xc4861b80 0x4000
249 blk.27.attn_output.weight 0xc4865b80 0xb00000
250 blk.27.attn_q.weight 0xc5365b80 0x540000
251 blk.27.attn_v.weight 0xc58a5b80 0x240000
252 blk.27.ffn_down.weight 0xc5ae5b80 0x1f80000
253 blk.27.ffn_gate.weight 0xc7a65b80 0x1260000
254 blk.27.ffn_norm.weight 0xc8cc5b80 0x4000
255 blk.27.ffn_up.weight 0xc8cc9b80 0x1260000
256 blk.28.attn_k.weight 0xc9f29b80 0x150000
257 blk.28.attn_norm.weight 0xca079b80 0x4000
258 blk.28.attn_output.weight 0xca07db80 0xb00000
259 blk.28.attn_q.weight 0xcab7db80 0x540000
260 blk.28.attn_v.weight 0xcb0bdb80 0x240000
261 blk.28.ffn_down.weight 0xcb2fdb80 0x1f80000
262 blk.28.ffn_gate.weight 0xcd27db80 0x1260000
263 blk.28.ffn_norm.weight 0xce4ddb80 0x4000
264 blk.28.ffn_up.weight 0xce4e1b80 0x1260000
265 blk.29.attn_k.weight 0xcf741b80 0x150000
266 blk.29.attn_norm.weight 0xcf891b80 0x4000
267 blk.29.attn_output.weight 0xcf895b80 0xb00000
268 blk.29.attn_q.weight 0xd0395b80 0x540000
269 blk.29.attn_v.weight 0xd08d5b80 0x240000
270 blk.29.ffn_down.weight 0xd0b15b80 0x1f80000
271 blk.29.ffn_gate.weight 0xd2a95b80 0x1260000
272 blk.29.ffn_norm.weight 0xd3cf5b80 0x4000
273 blk.29.ffn_up.weight 0xd3cf9b80 0x1260000
274 blk.30.attn_k.weight 0xd4f59b80 0x150000
275 blk.30.attn_norm.weight 0xd50a9b80 0x4000
276 blk.30.attn_output.weight 0xd50adb80 0xb00000
277 blk.30.attn_q.weight 0xd5badb80 0x540000
278 blk.30.attn_v.weight 0xd60edb80 0x240000
279 blk.30.ffn_down.weight 0xd632db80 0x1f80000
280 blk.30.ffn_gate.weight 0xd82adb80 0x1260000
281 blk.30.ffn_norm.weight 0xd950db80 0x4000
282 blk.30.ffn_up.weight 0xd9511b80 0x1260000
283 blk.31.attn_k.weight 0xda771b80 0x150000
284 blk.31.attn_norm.weight 0xda8c1b80 0x4000
285 blk.31.attn_output.weight 0xda8c5b80 0xb00000
286 blk.31.attn_q.weight 0xdb3c5b80 0x540000
287 blk.31.attn_v.weight 0xdb905b80 0x240000
288 blk.31.ffn_down.weight 0xdbb45b80 0x1f80000
289 blk.31.ffn_gate.weight 0xddac5b80 0x1260000
290 blk.31.ffn_norm.weight 0xded25b80 0x4000
291 blk.31.ffn_up.weight 0xded29b80 0x1260000

Base Tensor Group : ~1B Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
0 output.weight Output (W) (~525M) 525336576 4096 x 128256 x 1 x 1 Q3_K
1 output_norm.weight Output Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
2 rope_freqs.weight Rope_Freqs (W) ( 64) 64 64 x 1 x 1 x 1 F32
3 token_embd.weight Token Embedding (W) (~525M) 525336576 4096 x 128256 x 1 x 1 Q3_K
  • Total elements in base: ( ~1B) 1050677312
  • Percentage of total elements: 13.08%

Block 0 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
4 blk.0.attn_k.weight Block 0 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
5 blk.0.attn_norm.weight Block 0 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
6 blk.0.attn_output.weight Block 0 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
7 blk.0.attn_q.weight Block 0 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
8 blk.0.attn_v.weight Block 0 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
9 blk.0.ffn_down.weight Block 0 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
10 blk.0.ffn_gate.weight Block 0 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
11 blk.0.ffn_norm.weight Block 0 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
12 blk.0.ffn_up.weight Block 0 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.0: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 1 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
13 blk.1.attn_k.weight Block 1 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
14 blk.1.attn_norm.weight Block 1 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
15 blk.1.attn_output.weight Block 1 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
16 blk.1.attn_q.weight Block 1 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
17 blk.1.attn_v.weight Block 1 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
18 blk.1.ffn_down.weight Block 1 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
19 blk.1.ffn_gate.weight Block 1 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
20 blk.1.ffn_norm.weight Block 1 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
21 blk.1.ffn_up.weight Block 1 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.1: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 2 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
22 blk.2.attn_k.weight Block 2 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
23 blk.2.attn_norm.weight Block 2 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
24 blk.2.attn_output.weight Block 2 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
25 blk.2.attn_q.weight Block 2 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
26 blk.2.attn_v.weight Block 2 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
27 blk.2.ffn_down.weight Block 2 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
28 blk.2.ffn_gate.weight Block 2 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
29 blk.2.ffn_norm.weight Block 2 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
30 blk.2.ffn_up.weight Block 2 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.2: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 3 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
31 blk.3.attn_k.weight Block 3 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
32 blk.3.attn_norm.weight Block 3 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
33 blk.3.attn_output.weight Block 3 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
34 blk.3.attn_q.weight Block 3 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
35 blk.3.attn_v.weight Block 3 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
36 blk.3.ffn_down.weight Block 3 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
37 blk.3.ffn_gate.weight Block 3 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
38 blk.3.ffn_norm.weight Block 3 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
39 blk.3.ffn_up.weight Block 3 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.3: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 4 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
40 blk.4.attn_k.weight Block 4 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
41 blk.4.attn_norm.weight Block 4 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
42 blk.4.attn_output.weight Block 4 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
43 blk.4.attn_q.weight Block 4 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
44 blk.4.attn_v.weight Block 4 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
45 blk.4.ffn_down.weight Block 4 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
46 blk.4.ffn_gate.weight Block 4 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
47 blk.4.ffn_norm.weight Block 4 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
48 blk.4.ffn_up.weight Block 4 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.4: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 5 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
49 blk.5.attn_k.weight Block 5 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
50 blk.5.attn_norm.weight Block 5 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
51 blk.5.attn_output.weight Block 5 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
52 blk.5.attn_q.weight Block 5 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
53 blk.5.attn_v.weight Block 5 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
54 blk.5.ffn_down.weight Block 5 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
55 blk.5.ffn_gate.weight Block 5 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
56 blk.5.ffn_norm.weight Block 5 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
57 blk.5.ffn_up.weight Block 5 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.5: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 6 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
58 blk.6.attn_k.weight Block 6 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
59 blk.6.attn_norm.weight Block 6 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
60 blk.6.attn_output.weight Block 6 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
61 blk.6.attn_q.weight Block 6 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
62 blk.6.attn_v.weight Block 6 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
63 blk.6.ffn_down.weight Block 6 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
64 blk.6.ffn_gate.weight Block 6 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
65 blk.6.ffn_norm.weight Block 6 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
66 blk.6.ffn_up.weight Block 6 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.6: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 7 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
67 blk.7.attn_k.weight Block 7 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
68 blk.7.attn_norm.weight Block 7 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
69 blk.7.attn_output.weight Block 7 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
70 blk.7.attn_q.weight Block 7 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
71 blk.7.attn_v.weight Block 7 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
72 blk.7.ffn_down.weight Block 7 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
73 blk.7.ffn_gate.weight Block 7 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
74 blk.7.ffn_norm.weight Block 7 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
75 blk.7.ffn_up.weight Block 7 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.7: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 8 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
76 blk.8.attn_k.weight Block 8 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
77 blk.8.attn_norm.weight Block 8 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
78 blk.8.attn_output.weight Block 8 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
79 blk.8.attn_q.weight Block 8 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
80 blk.8.attn_v.weight Block 8 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
81 blk.8.ffn_down.weight Block 8 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
82 blk.8.ffn_gate.weight Block 8 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
83 blk.8.ffn_norm.weight Block 8 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
84 blk.8.ffn_up.weight Block 8 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.8: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 9 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
85 blk.9.attn_k.weight Block 9 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
86 blk.9.attn_norm.weight Block 9 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
87 blk.9.attn_output.weight Block 9 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
88 blk.9.attn_q.weight Block 9 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
89 blk.9.attn_v.weight Block 9 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
90 blk.9.ffn_down.weight Block 9 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
91 blk.9.ffn_gate.weight Block 9 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
92 blk.9.ffn_norm.weight Block 9 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
93 blk.9.ffn_up.weight Block 9 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.9: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 10 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
94 blk.10.attn_k.weight Block 10 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
95 blk.10.attn_norm.weight Block 10 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
96 blk.10.attn_output.weight Block 10 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
97 blk.10.attn_q.weight Block 10 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
98 blk.10.attn_v.weight Block 10 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
99 blk.10.ffn_down.weight Block 10 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
100 blk.10.ffn_gate.weight Block 10 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
101 blk.10.ffn_norm.weight Block 10 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
102 blk.10.ffn_up.weight Block 10 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.10: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 11 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
103 blk.11.attn_k.weight Block 11 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
104 blk.11.attn_norm.weight Block 11 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
105 blk.11.attn_output.weight Block 11 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
106 blk.11.attn_q.weight Block 11 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
107 blk.11.attn_v.weight Block 11 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
108 blk.11.ffn_down.weight Block 11 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
109 blk.11.ffn_gate.weight Block 11 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
110 blk.11.ffn_norm.weight Block 11 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
111 blk.11.ffn_up.weight Block 11 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.11: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 12 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
112 blk.12.attn_k.weight Block 12 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
113 blk.12.attn_norm.weight Block 12 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
114 blk.12.attn_output.weight Block 12 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
115 blk.12.attn_q.weight Block 12 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
116 blk.12.attn_v.weight Block 12 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
117 blk.12.ffn_down.weight Block 12 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
118 blk.12.ffn_gate.weight Block 12 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
119 blk.12.ffn_norm.weight Block 12 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
120 blk.12.ffn_up.weight Block 12 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.12: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 13 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
121 blk.13.attn_k.weight Block 13 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
122 blk.13.attn_norm.weight Block 13 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
123 blk.13.attn_output.weight Block 13 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
124 blk.13.attn_q.weight Block 13 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
125 blk.13.attn_v.weight Block 13 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
126 blk.13.ffn_down.weight Block 13 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
127 blk.13.ffn_gate.weight Block 13 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
128 blk.13.ffn_norm.weight Block 13 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
129 blk.13.ffn_up.weight Block 13 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.13: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 14 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
130 blk.14.attn_k.weight Block 14 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
131 blk.14.attn_norm.weight Block 14 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
132 blk.14.attn_output.weight Block 14 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
133 blk.14.attn_q.weight Block 14 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
134 blk.14.attn_v.weight Block 14 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
135 blk.14.ffn_down.weight Block 14 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
136 blk.14.ffn_gate.weight Block 14 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
137 blk.14.ffn_norm.weight Block 14 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
138 blk.14.ffn_up.weight Block 14 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.14: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 15 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
139 blk.15.attn_k.weight Block 15 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q3_K
140 blk.15.attn_norm.weight Block 15 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
141 blk.15.attn_output.weight Block 15 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
142 blk.15.attn_q.weight Block 15 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q3_K
143 blk.15.attn_v.weight Block 15 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
144 blk.15.ffn_down.weight Block 15 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q5_K
145 blk.15.ffn_gate.weight Block 15 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
146 blk.15.ffn_norm.weight Block 15 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
147 blk.15.ffn_up.weight Block 15 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q3_K
  • Total elements in blk.15: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 16 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
148 blk.16.attn_k.weight Block 16 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
149 blk.16.attn_norm.weight Block 16 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
150 blk.16.attn_output.weight Block 16 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
151 blk.16.attn_q.weight Block 16 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
152 blk.16.attn_v.weight Block 16 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
153 blk.16.ffn_down.weight Block 16 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
154 blk.16.ffn_gate.weight Block 16 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
155 blk.16.ffn_norm.weight Block 16 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
156 blk.16.ffn_up.weight Block 16 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.16: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 17 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
157 blk.17.attn_k.weight Block 17 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
158 blk.17.attn_norm.weight Block 17 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
159 blk.17.attn_output.weight Block 17 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
160 blk.17.attn_q.weight Block 17 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
161 blk.17.attn_v.weight Block 17 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
162 blk.17.ffn_down.weight Block 17 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
163 blk.17.ffn_gate.weight Block 17 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
164 blk.17.ffn_norm.weight Block 17 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
165 blk.17.ffn_up.weight Block 17 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.17: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 18 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
166 blk.18.attn_k.weight Block 18 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
167 blk.18.attn_norm.weight Block 18 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
168 blk.18.attn_output.weight Block 18 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
169 blk.18.attn_q.weight Block 18 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
170 blk.18.attn_v.weight Block 18 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
171 blk.18.ffn_down.weight Block 18 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
172 blk.18.ffn_gate.weight Block 18 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
173 blk.18.ffn_norm.weight Block 18 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
174 blk.18.ffn_up.weight Block 18 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.18: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 19 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
175 blk.19.attn_k.weight Block 19 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
176 blk.19.attn_norm.weight Block 19 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
177 blk.19.attn_output.weight Block 19 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
178 blk.19.attn_q.weight Block 19 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
179 blk.19.attn_v.weight Block 19 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
180 blk.19.ffn_down.weight Block 19 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
181 blk.19.ffn_gate.weight Block 19 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
182 blk.19.ffn_norm.weight Block 19 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
183 blk.19.ffn_up.weight Block 19 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.19: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 20 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
184 blk.20.attn_k.weight Block 20 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
185 blk.20.attn_norm.weight Block 20 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
186 blk.20.attn_output.weight Block 20 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
187 blk.20.attn_q.weight Block 20 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
188 blk.20.attn_v.weight Block 20 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
189 blk.20.ffn_down.weight Block 20 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
190 blk.20.ffn_gate.weight Block 20 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
191 blk.20.ffn_norm.weight Block 20 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
192 blk.20.ffn_up.weight Block 20 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.20: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 21 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
193 blk.21.attn_k.weight Block 21 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
194 blk.21.attn_norm.weight Block 21 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
195 blk.21.attn_output.weight Block 21 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
196 blk.21.attn_q.weight Block 21 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
197 blk.21.attn_v.weight Block 21 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
198 blk.21.ffn_down.weight Block 21 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
199 blk.21.ffn_gate.weight Block 21 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
200 blk.21.ffn_norm.weight Block 21 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
201 blk.21.ffn_up.weight Block 21 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.21: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 22 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
202 blk.22.attn_k.weight Block 22 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
203 blk.22.attn_norm.weight Block 22 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
204 blk.22.attn_output.weight Block 22 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
205 blk.22.attn_q.weight Block 22 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
206 blk.22.attn_v.weight Block 22 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
207 blk.22.ffn_down.weight Block 22 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
208 blk.22.ffn_gate.weight Block 22 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
209 blk.22.ffn_norm.weight Block 22 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
210 blk.22.ffn_up.weight Block 22 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.22: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 23 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
211 blk.23.attn_k.weight Block 23 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
212 blk.23.attn_norm.weight Block 23 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
213 blk.23.attn_output.weight Block 23 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
214 blk.23.attn_q.weight Block 23 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
215 blk.23.attn_v.weight Block 23 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
216 blk.23.ffn_down.weight Block 23 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
217 blk.23.ffn_gate.weight Block 23 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
218 blk.23.ffn_norm.weight Block 23 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
219 blk.23.ffn_up.weight Block 23 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.23: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 24 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
220 blk.24.attn_k.weight Block 24 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
221 blk.24.attn_norm.weight Block 24 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
222 blk.24.attn_output.weight Block 24 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
223 blk.24.attn_q.weight Block 24 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
224 blk.24.attn_v.weight Block 24 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
225 blk.24.ffn_down.weight Block 24 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
226 blk.24.ffn_gate.weight Block 24 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
227 blk.24.ffn_norm.weight Block 24 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
228 blk.24.ffn_up.weight Block 24 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.24: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 25 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
229 blk.25.attn_k.weight Block 25 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
230 blk.25.attn_norm.weight Block 25 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
231 blk.25.attn_output.weight Block 25 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
232 blk.25.attn_q.weight Block 25 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
233 blk.25.attn_v.weight Block 25 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
234 blk.25.ffn_down.weight Block 25 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
235 blk.25.ffn_gate.weight Block 25 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
236 blk.25.ffn_norm.weight Block 25 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
237 blk.25.ffn_up.weight Block 25 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.25: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 26 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
238 blk.26.attn_k.weight Block 26 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
239 blk.26.attn_norm.weight Block 26 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
240 blk.26.attn_output.weight Block 26 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
241 blk.26.attn_q.weight Block 26 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
242 blk.26.attn_v.weight Block 26 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
243 blk.26.ffn_down.weight Block 26 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
244 blk.26.ffn_gate.weight Block 26 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
245 blk.26.ffn_norm.weight Block 26 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
246 blk.26.ffn_up.weight Block 26 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.26: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 27 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
247 blk.27.attn_k.weight Block 27 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
248 blk.27.attn_norm.weight Block 27 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
249 blk.27.attn_output.weight Block 27 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
250 blk.27.attn_q.weight Block 27 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
251 blk.27.attn_v.weight Block 27 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
252 blk.27.ffn_down.weight Block 27 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
253 blk.27.ffn_gate.weight Block 27 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
254 blk.27.ffn_norm.weight Block 27 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
255 blk.27.ffn_up.weight Block 27 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.27: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 28 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
256 blk.28.attn_k.weight Block 28 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
257 blk.28.attn_norm.weight Block 28 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
258 blk.28.attn_output.weight Block 28 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
259 blk.28.attn_q.weight Block 28 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
260 blk.28.attn_v.weight Block 28 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
261 blk.28.ffn_down.weight Block 28 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
262 blk.28.ffn_gate.weight Block 28 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
263 blk.28.ffn_norm.weight Block 28 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
264 blk.28.ffn_up.weight Block 28 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.28: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 29 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
265 blk.29.attn_k.weight Block 29 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
266 blk.29.attn_norm.weight Block 29 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
267 blk.29.attn_output.weight Block 29 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
268 blk.29.attn_q.weight Block 29 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
269 blk.29.attn_v.weight Block 29 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
270 blk.29.ffn_down.weight Block 29 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
271 blk.29.ffn_gate.weight Block 29 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
272 blk.29.ffn_norm.weight Block 29 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
273 blk.29.ffn_up.weight Block 29 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.29: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 30 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
274 blk.30.attn_k.weight Block 30 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
275 blk.30.attn_norm.weight Block 30 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
276 blk.30.attn_output.weight Block 30 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
277 blk.30.attn_q.weight Block 30 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
278 blk.30.attn_v.weight Block 30 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
279 blk.30.ffn_down.weight Block 30 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
280 blk.30.ffn_gate.weight Block 30 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
281 blk.30.ffn_norm.weight Block 30 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
282 blk.30.ffn_up.weight Block 30 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.30: (~218M) 218112000
  • Percentage of total elements: 2.72%

Block 31 Tensor Group : ~218M Elements

T_ID Tensor Layer Name Human Friendly Tensor Layer Name Elements Shape Type
283 blk.31.attn_k.weight Block 31 Attention Key (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q2_K
284 blk.31.attn_norm.weight Block 31 Attention Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
285 blk.31.attn_output.weight Block 31 Attention Output (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q5_K
286 blk.31.attn_q.weight Block 31 Attention Query (W) (~17M) 16777216 4096 x 4096 x 1 x 1 Q2_K
287 blk.31.attn_v.weight Block 31 Attention Value (W) ( ~4M) 4194304 4096 x 1024 x 1 x 1 Q4_K
288 blk.31.ffn_down.weight Block 31 Feed-Forward Network "Down" (W) (~59M) 58720256 14336 x 4096 x 1 x 1 Q4_K
289 blk.31.ffn_gate.weight Block 31 Feed-Forward Network "Gate" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
290 blk.31.ffn_norm.weight Block 31 Feed-Forward Network Normalization (W) ( ~4K) 4096 4096 x 1 x 1 x 1 F32
291 blk.31.ffn_up.weight Block 31 Feed-Forward Network "Up" (W) (~59M) 58720256 4096 x 14336 x 1 x 1 Q2_K
  • Total elements in blk.31: (~218M) 218112000
  • Percentage of total elements: 2.72%