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ModelHub XC f9723b838e 初始化项目，由ModelHub XC社区提供模型

Model: eaddario/Watt-Tool-8B-GGUF
Source: Original Platform

2026-07-21 16:00:13 +08:00

83 KiB

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Watt-Tool-8B-Q6_K.gguf - GGUF Internal File Dump

Endian: LITTLE endian

Key Value Metadata Store

There are 43 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	40
4	STRING	1	general.architecture	`llama`
5	STRING	1	general.type	`model`
6	STRING	1	general.name	`Watt Tool 8B GGUF`
7	STRING	1	general.finetune	`GGUF`
8	STRING	1	general.basename	`Watt-Tool`
9	STRING	1	general.size_label	`8B`
10	STRING	1	general.license	`apache-2.0`
11	UINT32	1	general.base_model.count	1
12	STRING	1	general.base_model.0.name	`Llama 3.1 8B Instruct`
13	STRING	1	general.base_model.0.organization	`Meta Llama`
14	STRING	1	general.base_model.0.repo_url	`https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct`
15	[STRING]	4	general.tags	[ `function-calling`, `tool-use`, `llama`, `bfcl` ]
16	[STRING]	1	general.languages	[ `en` ]
17	UINT32	1	llama.block_count	32
18	UINT32	1	llama.context_length	131072
19	UINT32	1	llama.embedding_length	4096
20	UINT32	1	llama.feed_forward_length	14336
21	UINT32	1	llama.attention.head_count	32
22	UINT32	1	llama.attention.head_count_kv	8
23	FLOAT32	1	llama.rope.freq_base	500000.0
24	FLOAT32	1	llama.attention.layer_norm_rms_epsilon	1e-05
25	UINT32	1	llama.attention.key_length	128
26	UINT32	1	llama.attention.value_length	128
27	UINT32	1	llama.vocab_size	128256
28	UINT32	1	llama.rope.dimension_count	128
29	STRING	1	tokenizer.ggml.model	`gpt2`
30	STRING	1	tokenizer.ggml.pre	`llama-bpe`
31	[STRING]	128256	tokenizer.ggml.tokens	[ `!`, `"`, `#`, `$`, `%`, ... ]
32	[INT32]	128256	tokenizer.ggml.token_type	[ 1, 1, 1, 1, 1, 1, 1, ... ]
33	[STRING]	280147	tokenizer.ggml.merges	[ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]
34	UINT32	1	tokenizer.ggml.bos_token_id	128000
35	UINT32	1	tokenizer.ggml.eos_token_id	128009
36	UINT32	1	tokenizer.ggml.padding_token_id	128009
37	STRING	1	tokenizer.chat_template	`{{ '<
38	UINT32	1	general.quantization_version	2
39	UINT32	1	general.file_type	18
40	STRING	1	quantize.imatrix.file	`./imatrix/imatrix-Watt-Tool-8B-small.dat`
41	STRING	1	quantize.imatrix.dataset	`../../datasets/imatrix/calibration_eur_small.txt`
42	INT32	1	quantize.imatrix.entries_count	225
43	INT32	1	quantize.imatrix.chunks_count	962

Tensors Overview ~8B Elements

Total number of elements in all tensors: 8030261312 Elements

Watt-Tool-8B-Q6_K.gguf - GGUF Internal File Dump
- Key Value Metadata Store
- Tensors Overview ~8B 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	0x779620	0x19afa000
1	output_norm.weight	0x1a273620	0x4000
2	rope_freqs.weight	0x1a277620	0x100
3	token_embd.weight	0x1a277720	0xd746000
4	blk.0.attn_k.weight	0x279bd720	0x2c0000
5	blk.0.attn_norm.weight	0x27c7d720	0x4000
6	blk.0.attn_output.weight	0x27c81720	0xd20000
7	blk.0.attn_q.weight	0x289a1720	0xb00000
8	blk.0.attn_v.weight	0x294a1720	0x348000
9	blk.0.ffn_down.weight	0x297e9720	0x3b80000
10	blk.0.ffn_gate.weight	0x2d369720	0x2680000
11	blk.0.ffn_norm.weight	0x2f9e9720	0x4000
12	blk.0.ffn_up.weight	0x2f9ed720	0x2680000
13	blk.1.attn_k.weight	0x3206d720	0x2c0000
14	blk.1.attn_norm.weight	0x3232d720	0x4000
15	blk.1.attn_output.weight	0x32331720	0xd20000
16	blk.1.attn_q.weight	0x33051720	0xb00000
17	blk.1.attn_v.weight	0x33b51720	0x348000
18	blk.1.ffn_down.weight	0x33e99720	0x3b80000
19	blk.1.ffn_gate.weight	0x37a19720	0x2680000
20	blk.1.ffn_norm.weight	0x3a099720	0x4000
21	blk.1.ffn_up.weight	0x3a09d720	0x2680000
22	blk.2.attn_k.weight	0x3c71d720	0x2c0000
23	blk.2.attn_norm.weight	0x3c9dd720	0x4000
24	blk.2.attn_output.weight	0x3c9e1720	0xd20000
25	blk.2.attn_q.weight	0x3d701720	0xb00000
26	blk.2.attn_v.weight	0x3e201720	0x348000
27	blk.2.ffn_down.weight	0x3e549720	0x3b80000
28	blk.2.ffn_gate.weight	0x420c9720	0x2680000
29	blk.2.ffn_norm.weight	0x44749720	0x4000
30	blk.2.ffn_up.weight	0x4474d720	0x2680000
31	blk.3.attn_k.weight	0x46dcd720	0x2c0000
32	blk.3.attn_norm.weight	0x4708d720	0x4000
33	blk.3.attn_output.weight	0x47091720	0xd20000
34	blk.3.attn_q.weight	0x47db1720	0xb00000
35	blk.3.attn_v.weight	0x488b1720	0x348000
36	blk.3.ffn_down.weight	0x48bf9720	0x3b80000
37	blk.3.ffn_gate.weight	0x4c779720	0x2680000
38	blk.3.ffn_norm.weight	0x4edf9720	0x4000
39	blk.3.ffn_up.weight	0x4edfd720	0x2680000
40	blk.4.attn_k.weight	0x5147d720	0x2c0000
41	blk.4.attn_norm.weight	0x5173d720	0x4000
42	blk.4.attn_output.weight	0x51741720	0xd20000
43	blk.4.attn_q.weight	0x52461720	0xb00000
44	blk.4.attn_v.weight	0x52f61720	0x348000
45	blk.4.ffn_down.weight	0x532a9720	0x3b80000
46	blk.4.ffn_gate.weight	0x56e29720	0x2680000
47	blk.4.ffn_norm.weight	0x594a9720	0x4000
48	blk.4.ffn_up.weight	0x594ad720	0x2680000
49	blk.5.attn_k.weight	0x5bb2d720	0x2c0000
50	blk.5.attn_norm.weight	0x5bded720	0x4000
51	blk.5.attn_output.weight	0x5bdf1720	0xd20000
52	blk.5.attn_q.weight	0x5cb11720	0xb00000
53	blk.5.attn_v.weight	0x5d611720	0x348000
54	blk.5.ffn_down.weight	0x5d959720	0x3b80000
55	blk.5.ffn_gate.weight	0x614d9720	0x2680000
56	blk.5.ffn_norm.weight	0x63b59720	0x4000
57	blk.5.ffn_up.weight	0x63b5d720	0x2680000
58	blk.6.attn_k.weight	0x661dd720	0x2c0000
59	blk.6.attn_norm.weight	0x6649d720	0x4000
60	blk.6.attn_output.weight	0x664a1720	0xd20000
61	blk.6.attn_q.weight	0x671c1720	0xb00000
62	blk.6.attn_v.weight	0x67cc1720	0x348000
63	blk.6.ffn_down.weight	0x68009720	0x3b80000
64	blk.6.ffn_gate.weight	0x6bb89720	0x2680000
65	blk.6.ffn_norm.weight	0x6e209720	0x4000
66	blk.6.ffn_up.weight	0x6e20d720	0x2680000
67	blk.7.attn_k.weight	0x7088d720	0x2c0000
68	blk.7.attn_norm.weight	0x70b4d720	0x4000
69	blk.7.attn_output.weight	0x70b51720	0xd20000
70	blk.7.attn_q.weight	0x71871720	0xb00000
71	blk.7.attn_v.weight	0x72371720	0x348000
72	blk.7.ffn_down.weight	0x726b9720	0x3b80000
73	blk.7.ffn_gate.weight	0x76239720	0x2680000
74	blk.7.ffn_norm.weight	0x788b9720	0x4000
75	blk.7.ffn_up.weight	0x788bd720	0x2680000
76	blk.8.attn_k.weight	0x7af3d720	0x2c0000
77	blk.8.attn_norm.weight	0x7b1fd720	0x4000
78	blk.8.attn_output.weight	0x7b201720	0xd20000
79	blk.8.attn_q.weight	0x7bf21720	0xb00000
80	blk.8.attn_v.weight	0x7ca21720	0x348000
81	blk.8.ffn_down.weight	0x7cd69720	0x3b80000
82	blk.8.ffn_gate.weight	0x808e9720	0x2680000
83	blk.8.ffn_norm.weight	0x82f69720	0x4000
84	blk.8.ffn_up.weight	0x82f6d720	0x2680000
85	blk.9.attn_k.weight	0x855ed720	0x2c0000
86	blk.9.attn_norm.weight	0x858ad720	0x4000
87	blk.9.attn_output.weight	0x858b1720	0xd20000
88	blk.9.attn_q.weight	0x865d1720	0xb00000
89	blk.9.attn_v.weight	0x870d1720	0x348000
90	blk.9.ffn_down.weight	0x87419720	0x3b80000
91	blk.9.ffn_gate.weight	0x8af99720	0x2680000
92	blk.9.ffn_norm.weight	0x8d619720	0x4000
93	blk.9.ffn_up.weight	0x8d61d720	0x2680000
94	blk.10.attn_k.weight	0x8fc9d720	0x2c0000
95	blk.10.attn_norm.weight	0x8ff5d720	0x4000
96	blk.10.attn_output.weight	0x8ff61720	0xd20000
97	blk.10.attn_q.weight	0x90c81720	0xb00000
98	blk.10.attn_v.weight	0x91781720	0x348000
99	blk.10.ffn_down.weight	0x91ac9720	0x3b80000
100	blk.10.ffn_gate.weight	0x95649720	0x2680000
101	blk.10.ffn_norm.weight	0x97cc9720	0x4000
102	blk.10.ffn_up.weight	0x97ccd720	0x2680000
103	blk.11.attn_k.weight	0x9a34d720	0x2c0000
104	blk.11.attn_norm.weight	0x9a60d720	0x4000
105	blk.11.attn_output.weight	0x9a611720	0xd20000
106	blk.11.attn_q.weight	0x9b331720	0xb00000
107	blk.11.attn_v.weight	0x9be31720	0x348000
108	blk.11.ffn_down.weight	0x9c179720	0x3b80000
109	blk.11.ffn_gate.weight	0x9fcf9720	0x2680000
110	blk.11.ffn_norm.weight	0xa2379720	0x4000
111	blk.11.ffn_up.weight	0xa237d720	0x2680000
112	blk.12.attn_k.weight	0xa49fd720	0x2c0000
113	blk.12.attn_norm.weight	0xa4cbd720	0x4000
114	blk.12.attn_output.weight	0xa4cc1720	0xd20000
115	blk.12.attn_q.weight	0xa59e1720	0xb00000
116	blk.12.attn_v.weight	0xa64e1720	0x348000
117	blk.12.ffn_down.weight	0xa6829720	0x3b80000
118	blk.12.ffn_gate.weight	0xaa3a9720	0x2680000
119	blk.12.ffn_norm.weight	0xaca29720	0x4000
120	blk.12.ffn_up.weight	0xaca2d720	0x2680000
121	blk.13.attn_k.weight	0xaf0ad720	0x348000
122	blk.13.attn_norm.weight	0xaf3f5720	0x4000
123	blk.13.attn_output.weight	0xaf3f9720	0xd20000
124	blk.13.attn_q.weight	0xb0119720	0xd20000
125	blk.13.attn_v.weight	0xb0e39720	0x440000
126	blk.13.ffn_down.weight	0xb1279720	0x3b80000
127	blk.13.ffn_gate.weight	0xb4df9720	0x2680000
128	blk.13.ffn_norm.weight	0xb7479720	0x4000
129	blk.13.ffn_up.weight	0xb747d720	0x2680000
130	blk.14.attn_k.weight	0xb9afd720	0x348000
131	blk.14.attn_norm.weight	0xb9e45720	0x4000
132	blk.14.attn_output.weight	0xb9e49720	0xd20000
133	blk.14.attn_q.weight	0xbab69720	0xd20000
134	blk.14.attn_v.weight	0xbb889720	0x440000
135	blk.14.ffn_down.weight	0xbbcc9720	0x3b80000
136	blk.14.ffn_gate.weight	0xbf849720	0x2680000
137	blk.14.ffn_norm.weight	0xc1ec9720	0x4000
138	blk.14.ffn_up.weight	0xc1ecd720	0x2680000
139	blk.15.attn_k.weight	0xc454d720	0x2c0000
140	blk.15.attn_norm.weight	0xc480d720	0x4000
141	blk.15.attn_output.weight	0xc4811720	0xd20000
142	blk.15.attn_q.weight	0xc5531720	0xb00000
143	blk.15.attn_v.weight	0xc6031720	0x348000
144	blk.15.ffn_down.weight	0xc6379720	0x3b80000
145	blk.15.ffn_gate.weight	0xc9ef9720	0x2680000
146	blk.15.ffn_norm.weight	0xcc579720	0x4000
147	blk.15.ffn_up.weight	0xcc57d720	0x2680000
148	blk.16.attn_k.weight	0xcebfd720	0x348000
149	blk.16.attn_norm.weight	0xcef45720	0x4000
150	blk.16.attn_output.weight	0xcef49720	0xd20000
151	blk.16.attn_q.weight	0xcfc69720	0xd20000
152	blk.16.attn_v.weight	0xd0989720	0x440000
153	blk.16.ffn_down.weight	0xd0dc9720	0x3b80000
154	blk.16.ffn_gate.weight	0xd4949720	0x2df0000
155	blk.16.ffn_norm.weight	0xd7739720	0x4000
156	blk.16.ffn_up.weight	0xd773d720	0x2df0000
157	blk.17.attn_k.weight	0xda52d720	0x2c0000
158	blk.17.attn_norm.weight	0xda7ed720	0x4000
159	blk.17.attn_output.weight	0xda7f1720	0xd20000
160	blk.17.attn_q.weight	0xdb511720	0xb00000
161	blk.17.attn_v.weight	0xdc011720	0x348000
162	blk.17.ffn_down.weight	0xdc359720	0x3b80000
163	blk.17.ffn_gate.weight	0xdfed9720	0x2df0000
164	blk.17.ffn_norm.weight	0xe2cc9720	0x4000
165	blk.17.ffn_up.weight	0xe2ccd720	0x2df0000
166	blk.18.attn_k.weight	0xe5abd720	0x348000
167	blk.18.attn_norm.weight	0xe5e05720	0x4000
168	blk.18.attn_output.weight	0xe5e09720	0xd20000
169	blk.18.attn_q.weight	0xe6b29720	0xd20000
170	blk.18.attn_v.weight	0xe7849720	0x440000
171	blk.18.ffn_down.weight	0xe7c89720	0x3b80000
172	blk.18.ffn_gate.weight	0xeb809720	0x2df0000
173	blk.18.ffn_norm.weight	0xee5f9720	0x4000
174	blk.18.ffn_up.weight	0xee5fd720	0x2df0000
175	blk.19.attn_k.weight	0xf13ed720	0x348000
176	blk.19.attn_norm.weight	0xf1735720	0x4000
177	blk.19.attn_output.weight	0xf1739720	0xd20000
178	blk.19.attn_q.weight	0xf2459720	0xd20000
179	blk.19.attn_v.weight	0xf3179720	0x440000
180	blk.19.ffn_down.weight	0xf35b9720	0x3b80000
181	blk.19.ffn_gate.weight	0xf7139720	0x2df0000
182	blk.19.ffn_norm.weight	0xf9f29720	0x4000
183	blk.19.ffn_up.weight	0xf9f2d720	0x2df0000
184	blk.20.attn_k.weight	0xfcd1d720	0x348000
185	blk.20.attn_norm.weight	0xfd065720	0x4000
186	blk.20.attn_output.weight	0xfd069720	0xd20000
187	blk.20.attn_q.weight	0xfdd89720	0xd20000
188	blk.20.attn_v.weight	0xfeaa9720	0x440000
189	blk.20.ffn_down.weight	0xfeee9720	0x3b80000
190	blk.20.ffn_gate.weight	0x102a69720	0x2df0000
191	blk.20.ffn_norm.weight	0x105859720	0x4000
192	blk.20.ffn_up.weight	0x10585d720	0x2df0000
193	blk.21.attn_k.weight	0x10864d720	0x348000
194	blk.21.attn_norm.weight	0x108995720	0x4000
195	blk.21.attn_output.weight	0x108999720	0xd20000
196	blk.21.attn_q.weight	0x1096b9720	0xd20000
197	blk.21.attn_v.weight	0x10a3d9720	0x440000
198	blk.21.ffn_down.weight	0x10a819720	0x3b80000
199	blk.21.ffn_gate.weight	0x10e399720	0x2df0000
200	blk.21.ffn_norm.weight	0x111189720	0x4000
201	blk.21.ffn_up.weight	0x11118d720	0x2df0000
202	blk.22.attn_k.weight	0x113f7d720	0x348000
203	blk.22.attn_norm.weight	0x1142c5720	0x4000
204	blk.22.attn_output.weight	0x1142c9720	0xd20000
205	blk.22.attn_q.weight	0x114fe9720	0xd20000
206	blk.22.attn_v.weight	0x115d09720	0x440000
207	blk.22.ffn_down.weight	0x116149720	0x3b80000
208	blk.22.ffn_gate.weight	0x119cc9720	0x2df0000
209	blk.22.ffn_norm.weight	0x11cab9720	0x4000
210	blk.22.ffn_up.weight	0x11cabd720	0x2df0000
211	blk.23.attn_k.weight	0x11f8ad720	0x348000
212	blk.23.attn_norm.weight	0x11fbf5720	0x4000
213	blk.23.attn_output.weight	0x11fbf9720	0xd20000
214	blk.23.attn_q.weight	0x120919720	0xd20000
215	blk.23.attn_v.weight	0x121639720	0x440000
216	blk.23.ffn_down.weight	0x121a79720	0x3b80000
217	blk.23.ffn_gate.weight	0x1255f9720	0x2df0000
218	blk.23.ffn_norm.weight	0x1283e9720	0x4000
219	blk.23.ffn_up.weight	0x1283ed720	0x2df0000
220	blk.24.attn_k.weight	0x12b1dd720	0x348000
221	blk.24.attn_norm.weight	0x12b525720	0x4000
222	blk.24.attn_output.weight	0x12b529720	0xd20000
223	blk.24.attn_q.weight	0x12c249720	0xd20000
224	blk.24.attn_v.weight	0x12cf69720	0x440000
225	blk.24.ffn_down.weight	0x12d3a9720	0x3b80000
226	blk.24.ffn_gate.weight	0x130f29720	0x2df0000
227	blk.24.ffn_norm.weight	0x133d19720	0x4000
228	blk.24.ffn_up.weight	0x133d1d720	0x2df0000
229	blk.25.attn_k.weight	0x136b0d720	0x348000
230	blk.25.attn_norm.weight	0x136e55720	0x4000
231	blk.25.attn_output.weight	0x136e59720	0xd20000
232	blk.25.attn_q.weight	0x137b79720	0xd20000
233	blk.25.attn_v.weight	0x138899720	0x440000
234	blk.25.ffn_down.weight	0x138cd9720	0x3b80000
235	blk.25.ffn_gate.weight	0x13c859720	0x2df0000
236	blk.25.ffn_norm.weight	0x13f649720	0x4000
237	blk.25.ffn_up.weight	0x13f64d720	0x2df0000
238	blk.26.attn_k.weight	0x14243d720	0x348000
239	blk.26.attn_norm.weight	0x142785720	0x4000
240	blk.26.attn_output.weight	0x142789720	0xd20000
241	blk.26.attn_q.weight	0x1434a9720	0xd20000
242	blk.26.attn_v.weight	0x1441c9720	0x440000
243	blk.26.ffn_down.weight	0x144609720	0x3b80000
244	blk.26.ffn_gate.weight	0x148189720	0x2df0000
245	blk.26.ffn_norm.weight	0x14af79720	0x4000
246	blk.26.ffn_up.weight	0x14af7d720	0x2df0000
247	blk.27.attn_k.weight	0x14dd6d720	0x348000
248	blk.27.attn_norm.weight	0x14e0b5720	0x4000
249	blk.27.attn_output.weight	0x14e0b9720	0xd20000
250	blk.27.attn_q.weight	0x14edd9720	0xd20000
251	blk.27.attn_v.weight	0x14faf9720	0x440000
252	blk.27.ffn_down.weight	0x14ff39720	0x3b80000
253	blk.27.ffn_gate.weight	0x153ab9720	0x2df0000
254	blk.27.ffn_norm.weight	0x1568a9720	0x4000
255	blk.27.ffn_up.weight	0x1568ad720	0x2df0000
256	blk.28.attn_k.weight	0x15969d720	0x348000
257	blk.28.attn_norm.weight	0x1599e5720	0x4000
258	blk.28.attn_output.weight	0x1599e9720	0xd20000
259	blk.28.attn_q.weight	0x15a709720	0xd20000
260	blk.28.attn_v.weight	0x15b429720	0x440000
261	blk.28.ffn_down.weight	0x15b869720	0x3b80000
262	blk.28.ffn_gate.weight	0x15f3e9720	0x2df0000
263	blk.28.ffn_norm.weight	0x1621d9720	0x4000
264	blk.28.ffn_up.weight	0x1621dd720	0x2df0000
265	blk.29.attn_k.weight	0x164fcd720	0x348000
266	blk.29.attn_norm.weight	0x165315720	0x4000
267	blk.29.attn_output.weight	0x165319720	0xd20000
268	blk.29.attn_q.weight	0x166039720	0xd20000
269	blk.29.attn_v.weight	0x166d59720	0x440000
270	blk.29.ffn_down.weight	0x167199720	0x3b80000
271	blk.29.ffn_gate.weight	0x16ad19720	0x2df0000
272	blk.29.ffn_norm.weight	0x16db09720	0x4000
273	blk.29.ffn_up.weight	0x16db0d720	0x2df0000
274	blk.30.attn_k.weight	0x1708fd720	0x348000
275	blk.30.attn_norm.weight	0x170c45720	0x4000
276	blk.30.attn_output.weight	0x170c49720	0xd20000
277	blk.30.attn_q.weight	0x171969720	0xd20000
278	blk.30.attn_v.weight	0x172689720	0x440000
279	blk.30.ffn_down.weight	0x172ac9720	0x3b80000
280	blk.30.ffn_gate.weight	0x176649720	0x2df0000
281	blk.30.ffn_norm.weight	0x179439720	0x4000
282	blk.30.ffn_up.weight	0x17943d720	0x2df0000
283	blk.31.attn_k.weight	0x17c22d720	0x2c0000
284	blk.31.attn_norm.weight	0x17c4ed720	0x4000
285	blk.31.attn_output.weight	0x17c4f1720	0xd20000
286	blk.31.attn_q.weight	0x17d211720	0xb00000
287	blk.31.attn_v.weight	0x17dd11720	0x348000
288	blk.31.ffn_down.weight	0x17e059720	0x3b80000
289	blk.31.ffn_gate.weight	0x181bd9720	0x2df0000
290	blk.31.ffn_norm.weight	0x1849c9720	0x4000
291	blk.31.ffn_up.weight	0x1849cd720	0x2df0000

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	Q6_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	Q5_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	Q6_K
7	blk.0.attn_q.weight	Block 0 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
8	blk.0.attn_v.weight	Block 0 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
9	blk.0.ffn_down.weight	Block 0 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
10	blk.0.ffn_gate.weight	Block 0 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
16	blk.1.attn_q.weight	Block 1 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
17	blk.1.attn_v.weight	Block 1 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
18	blk.1.ffn_down.weight	Block 1 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
19	blk.1.ffn_gate.weight	Block 1 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
25	blk.2.attn_q.weight	Block 2 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
26	blk.2.attn_v.weight	Block 2 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
27	blk.2.ffn_down.weight	Block 2 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
28	blk.2.ffn_gate.weight	Block 2 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
34	blk.3.attn_q.weight	Block 3 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
35	blk.3.attn_v.weight	Block 3 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
36	blk.3.ffn_down.weight	Block 3 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
37	blk.3.ffn_gate.weight	Block 3 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
43	blk.4.attn_q.weight	Block 4 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
44	blk.4.attn_v.weight	Block 4 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
45	blk.4.ffn_down.weight	Block 4 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
46	blk.4.ffn_gate.weight	Block 4 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
52	blk.5.attn_q.weight	Block 5 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
53	blk.5.attn_v.weight	Block 5 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
54	blk.5.ffn_down.weight	Block 5 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
55	blk.5.ffn_gate.weight	Block 5 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
61	blk.6.attn_q.weight	Block 6 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
62	blk.6.attn_v.weight	Block 6 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
63	blk.6.ffn_down.weight	Block 6 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
64	blk.6.ffn_gate.weight	Block 6 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
70	blk.7.attn_q.weight	Block 7 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
71	blk.7.attn_v.weight	Block 7 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
72	blk.7.ffn_down.weight	Block 7 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
73	blk.7.ffn_gate.weight	Block 7 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
79	blk.8.attn_q.weight	Block 8 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
80	blk.8.attn_v.weight	Block 8 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
81	blk.8.ffn_down.weight	Block 8 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
82	blk.8.ffn_gate.weight	Block 8 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
88	blk.9.attn_q.weight	Block 9 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
89	blk.9.attn_v.weight	Block 9 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
90	blk.9.ffn_down.weight	Block 9 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
91	blk.9.ffn_gate.weight	Block 9 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
97	blk.10.attn_q.weight	Block 10 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
98	blk.10.attn_v.weight	Block 10 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
99	blk.10.ffn_down.weight	Block 10 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
100	blk.10.ffn_gate.weight	Block 10 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
106	blk.11.attn_q.weight	Block 11 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
107	blk.11.attn_v.weight	Block 11 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
108	blk.11.ffn_down.weight	Block 11 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
109	blk.11.ffn_gate.weight	Block 11 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
115	blk.12.attn_q.weight	Block 12 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
116	blk.12.attn_v.weight	Block 12 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
117	blk.12.ffn_down.weight	Block 12 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
118	blk.12.ffn_gate.weight	Block 12 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q6_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	Q6_K
124	blk.13.attn_q.weight	Block 13 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
125	blk.13.attn_v.weight	Block 13 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
126	blk.13.ffn_down.weight	Block 13 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
127	blk.13.ffn_gate.weight	Block 13 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q6_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	Q6_K
133	blk.14.attn_q.weight	Block 14 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
134	blk.14.attn_v.weight	Block 14 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
135	blk.14.ffn_down.weight	Block 14 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
136	blk.14.ffn_gate.weight	Block 14 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q5_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	Q6_K
142	blk.15.attn_q.weight	Block 15 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
143	blk.15.attn_v.weight	Block 15 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
144	blk.15.ffn_down.weight	Block 15 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
145	blk.15.ffn_gate.weight	Block 15 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q5_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	Q5_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	Q6_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	Q6_K
151	blk.16.attn_q.weight	Block 16 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
152	blk.16.attn_v.weight	Block 16 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
153	blk.16.ffn_down.weight	Block 16 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
154	blk.16.ffn_gate.weight	Block 16 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q5_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	Q6_K
160	blk.17.attn_q.weight	Block 17 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
161	blk.17.attn_v.weight	Block 17 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
162	blk.17.ffn_down.weight	Block 17 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
163	blk.17.ffn_gate.weight	Block 17 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
169	blk.18.attn_q.weight	Block 18 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
170	blk.18.attn_v.weight	Block 18 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
171	blk.18.ffn_down.weight	Block 18 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
172	blk.18.ffn_gate.weight	Block 18 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
178	blk.19.attn_q.weight	Block 19 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
179	blk.19.attn_v.weight	Block 19 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
180	blk.19.ffn_down.weight	Block 19 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
181	blk.19.ffn_gate.weight	Block 19 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
187	blk.20.attn_q.weight	Block 20 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
188	blk.20.attn_v.weight	Block 20 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
189	blk.20.ffn_down.weight	Block 20 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
190	blk.20.ffn_gate.weight	Block 20 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
196	blk.21.attn_q.weight	Block 21 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
197	blk.21.attn_v.weight	Block 21 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
198	blk.21.ffn_down.weight	Block 21 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
199	blk.21.ffn_gate.weight	Block 21 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
205	blk.22.attn_q.weight	Block 22 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
206	blk.22.attn_v.weight	Block 22 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
207	blk.22.ffn_down.weight	Block 22 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
208	blk.22.ffn_gate.weight	Block 22 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
214	blk.23.attn_q.weight	Block 23 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
215	blk.23.attn_v.weight	Block 23 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
216	blk.23.ffn_down.weight	Block 23 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
217	blk.23.ffn_gate.weight	Block 23 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
223	blk.24.attn_q.weight	Block 24 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
224	blk.24.attn_v.weight	Block 24 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
225	blk.24.ffn_down.weight	Block 24 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
226	blk.24.ffn_gate.weight	Block 24 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
232	blk.25.attn_q.weight	Block 25 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
233	blk.25.attn_v.weight	Block 25 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
234	blk.25.ffn_down.weight	Block 25 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
235	blk.25.ffn_gate.weight	Block 25 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
241	blk.26.attn_q.weight	Block 26 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
242	blk.26.attn_v.weight	Block 26 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
243	blk.26.ffn_down.weight	Block 26 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
244	blk.26.ffn_gate.weight	Block 26 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
250	blk.27.attn_q.weight	Block 27 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
251	blk.27.attn_v.weight	Block 27 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
252	blk.27.ffn_down.weight	Block 27 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
253	blk.27.ffn_gate.weight	Block 27 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
259	blk.28.attn_q.weight	Block 28 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
260	blk.28.attn_v.weight	Block 28 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
261	blk.28.ffn_down.weight	Block 28 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
262	blk.28.ffn_gate.weight	Block 28 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
268	blk.29.attn_q.weight	Block 29 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
269	blk.29.attn_v.weight	Block 29 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
270	blk.29.ffn_down.weight	Block 29 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
271	blk.29.ffn_gate.weight	Block 29 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q6_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	Q6_K
277	blk.30.attn_q.weight	Block 30 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
278	blk.30.attn_v.weight	Block 30 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
279	blk.30.ffn_down.weight	Block 30 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
280	blk.30.ffn_gate.weight	Block 30 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_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	Q5_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	Q6_K
286	blk.31.attn_q.weight	Block 31 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q5_K
287	blk.31.attn_v.weight	Block 31 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q6_K
288	blk.31.ffn_down.weight	Block 31 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	Q8_0
289	blk.31.ffn_gate.weight	Block 31 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	Q6_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	Q6_K

Total elements in blk.31: (~218M) 218112000
Percentage of total elements: 2.72%

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Watt-Tool-8B-Q6_K.gguf - GGUF Internal File Dump

Key Value Metadata Store

Tensors Overview ~8B Elements

Tensor Data Offset

83 KiB

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