Files

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-Q8_0.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	7
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-Q8_0.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	0x21450000
1	output_norm.weight	0x21bc9620	0x4000
2	rope_freqs.weight	0x21bcd620	0x100
3	token_embd.weight	0x21bcd720	0xd746000
4	blk.0.attn_k.weight	0x2f313720	0x348000
5	blk.0.attn_norm.weight	0x2f65b720	0x4000
6	blk.0.attn_output.weight	0x2f65f720	0x1100000
7	blk.0.attn_q.weight	0x3075f720	0xd20000
8	blk.0.attn_v.weight	0x3147f720	0x440000
9	blk.0.ffn_down.weight	0x318bf720	0x3b80000
10	blk.0.ffn_gate.weight	0x3543f720	0x2df0000
11	blk.0.ffn_norm.weight	0x3822f720	0x4000
12	blk.0.ffn_up.weight	0x38233720	0x2df0000
13	blk.1.attn_k.weight	0x3b023720	0x348000
14	blk.1.attn_norm.weight	0x3b36b720	0x4000
15	blk.1.attn_output.weight	0x3b36f720	0x1100000
16	blk.1.attn_q.weight	0x3c46f720	0xd20000
17	blk.1.attn_v.weight	0x3d18f720	0x440000
18	blk.1.ffn_down.weight	0x3d5cf720	0x3b80000
19	blk.1.ffn_gate.weight	0x4114f720	0x2df0000
20	blk.1.ffn_norm.weight	0x43f3f720	0x4000
21	blk.1.ffn_up.weight	0x43f43720	0x2df0000
22	blk.2.attn_k.weight	0x46d33720	0x348000
23	blk.2.attn_norm.weight	0x4707b720	0x4000
24	blk.2.attn_output.weight	0x4707f720	0x1100000
25	blk.2.attn_q.weight	0x4817f720	0xd20000
26	blk.2.attn_v.weight	0x48e9f720	0x440000
27	blk.2.ffn_down.weight	0x492df720	0x3b80000
28	blk.2.ffn_gate.weight	0x4ce5f720	0x2df0000
29	blk.2.ffn_norm.weight	0x4fc4f720	0x4000
30	blk.2.ffn_up.weight	0x4fc53720	0x2df0000
31	blk.3.attn_k.weight	0x52a43720	0x348000
32	blk.3.attn_norm.weight	0x52d8b720	0x4000
33	blk.3.attn_output.weight	0x52d8f720	0x1100000
34	blk.3.attn_q.weight	0x53e8f720	0xd20000
35	blk.3.attn_v.weight	0x54baf720	0x440000
36	blk.3.ffn_down.weight	0x54fef720	0x3b80000
37	blk.3.ffn_gate.weight	0x58b6f720	0x2df0000
38	blk.3.ffn_norm.weight	0x5b95f720	0x4000
39	blk.3.ffn_up.weight	0x5b963720	0x2df0000
40	blk.4.attn_k.weight	0x5e753720	0x348000
41	blk.4.attn_norm.weight	0x5ea9b720	0x4000
42	blk.4.attn_output.weight	0x5ea9f720	0x1100000
43	blk.4.attn_q.weight	0x5fb9f720	0xd20000
44	blk.4.attn_v.weight	0x608bf720	0x440000
45	blk.4.ffn_down.weight	0x60cff720	0x3b80000
46	blk.4.ffn_gate.weight	0x6487f720	0x2df0000
47	blk.4.ffn_norm.weight	0x6766f720	0x4000
48	blk.4.ffn_up.weight	0x67673720	0x2df0000
49	blk.5.attn_k.weight	0x6a463720	0x348000
50	blk.5.attn_norm.weight	0x6a7ab720	0x4000
51	blk.5.attn_output.weight	0x6a7af720	0x1100000
52	blk.5.attn_q.weight	0x6b8af720	0xd20000
53	blk.5.attn_v.weight	0x6c5cf720	0x440000
54	blk.5.ffn_down.weight	0x6ca0f720	0x3b80000
55	blk.5.ffn_gate.weight	0x7058f720	0x2df0000
56	blk.5.ffn_norm.weight	0x7337f720	0x4000
57	blk.5.ffn_up.weight	0x73383720	0x2df0000
58	blk.6.attn_k.weight	0x76173720	0x348000
59	blk.6.attn_norm.weight	0x764bb720	0x4000
60	blk.6.attn_output.weight	0x764bf720	0x1100000
61	blk.6.attn_q.weight	0x775bf720	0xd20000
62	blk.6.attn_v.weight	0x782df720	0x440000
63	blk.6.ffn_down.weight	0x7871f720	0x3b80000
64	blk.6.ffn_gate.weight	0x7c29f720	0x2df0000
65	blk.6.ffn_norm.weight	0x7f08f720	0x4000
66	blk.6.ffn_up.weight	0x7f093720	0x2df0000
67	blk.7.attn_k.weight	0x81e83720	0x348000
68	blk.7.attn_norm.weight	0x821cb720	0x4000
69	blk.7.attn_output.weight	0x821cf720	0x1100000
70	blk.7.attn_q.weight	0x832cf720	0xd20000
71	blk.7.attn_v.weight	0x83fef720	0x440000
72	blk.7.ffn_down.weight	0x8442f720	0x3b80000
73	blk.7.ffn_gate.weight	0x87faf720	0x2df0000
74	blk.7.ffn_norm.weight	0x8ad9f720	0x4000
75	blk.7.ffn_up.weight	0x8ada3720	0x2df0000
76	blk.8.attn_k.weight	0x8db93720	0x348000
77	blk.8.attn_norm.weight	0x8dedb720	0x4000
78	blk.8.attn_output.weight	0x8dedf720	0x1100000
79	blk.8.attn_q.weight	0x8efdf720	0xd20000
80	blk.8.attn_v.weight	0x8fcff720	0x440000
81	blk.8.ffn_down.weight	0x9013f720	0x3b80000
82	blk.8.ffn_gate.weight	0x93cbf720	0x2df0000
83	blk.8.ffn_norm.weight	0x96aaf720	0x4000
84	blk.8.ffn_up.weight	0x96ab3720	0x2df0000
85	blk.9.attn_k.weight	0x998a3720	0x348000
86	blk.9.attn_norm.weight	0x99beb720	0x4000
87	blk.9.attn_output.weight	0x99bef720	0x1100000
88	blk.9.attn_q.weight	0x9acef720	0xd20000
89	blk.9.attn_v.weight	0x9ba0f720	0x440000
90	blk.9.ffn_down.weight	0x9be4f720	0x3b80000
91	blk.9.ffn_gate.weight	0x9f9cf720	0x2df0000
92	blk.9.ffn_norm.weight	0xa27bf720	0x4000
93	blk.9.ffn_up.weight	0xa27c3720	0x2df0000
94	blk.10.attn_k.weight	0xa55b3720	0x348000
95	blk.10.attn_norm.weight	0xa58fb720	0x4000
96	blk.10.attn_output.weight	0xa58ff720	0x1100000
97	blk.10.attn_q.weight	0xa69ff720	0xd20000
98	blk.10.attn_v.weight	0xa771f720	0x440000
99	blk.10.ffn_down.weight	0xa7b5f720	0x3b80000
100	blk.10.ffn_gate.weight	0xab6df720	0x2df0000
101	blk.10.ffn_norm.weight	0xae4cf720	0x4000
102	blk.10.ffn_up.weight	0xae4d3720	0x2df0000
103	blk.11.attn_k.weight	0xb12c3720	0x348000
104	blk.11.attn_norm.weight	0xb160b720	0x4000
105	blk.11.attn_output.weight	0xb160f720	0x1100000
106	blk.11.attn_q.weight	0xb270f720	0xd20000
107	blk.11.attn_v.weight	0xb342f720	0x440000
108	blk.11.ffn_down.weight	0xb386f720	0x3b80000
109	blk.11.ffn_gate.weight	0xb73ef720	0x2df0000
110	blk.11.ffn_norm.weight	0xba1df720	0x4000
111	blk.11.ffn_up.weight	0xba1e3720	0x2df0000
112	blk.12.attn_k.weight	0xbcfd3720	0x348000
113	blk.12.attn_norm.weight	0xbd31b720	0x4000
114	blk.12.attn_output.weight	0xbd31f720	0x1100000
115	blk.12.attn_q.weight	0xbe41f720	0xd20000
116	blk.12.attn_v.weight	0xbf13f720	0x440000
117	blk.12.ffn_down.weight	0xbf57f720	0x3b80000
118	blk.12.ffn_gate.weight	0xc30ff720	0x2df0000
119	blk.12.ffn_norm.weight	0xc5eef720	0x4000
120	blk.12.ffn_up.weight	0xc5ef3720	0x2df0000
121	blk.13.attn_k.weight	0xc8ce3720	0x440000
122	blk.13.attn_norm.weight	0xc9123720	0x4000
123	blk.13.attn_output.weight	0xc9127720	0x1100000
124	blk.13.attn_q.weight	0xca227720	0x1100000
125	blk.13.attn_v.weight	0xcb327720	0x800000
126	blk.13.ffn_down.weight	0xcbb27720	0x3b80000
127	blk.13.ffn_gate.weight	0xcf6a7720	0x2df0000
128	blk.13.ffn_norm.weight	0xd2497720	0x4000
129	blk.13.ffn_up.weight	0xd249b720	0x2df0000
130	blk.14.attn_k.weight	0xd528b720	0x440000
131	blk.14.attn_norm.weight	0xd56cb720	0x4000
132	blk.14.attn_output.weight	0xd56cf720	0x1100000
133	blk.14.attn_q.weight	0xd67cf720	0x1100000
134	blk.14.attn_v.weight	0xd78cf720	0x800000
135	blk.14.ffn_down.weight	0xd80cf720	0x3b80000
136	blk.14.ffn_gate.weight	0xdbc4f720	0x2df0000
137	blk.14.ffn_norm.weight	0xdea3f720	0x4000
138	blk.14.ffn_up.weight	0xdea43720	0x2df0000
139	blk.15.attn_k.weight	0xe1833720	0x348000
140	blk.15.attn_norm.weight	0xe1b7b720	0x4000
141	blk.15.attn_output.weight	0xe1b7f720	0x1100000
142	blk.15.attn_q.weight	0xe2c7f720	0xd20000
143	blk.15.attn_v.weight	0xe399f720	0x440000
144	blk.15.ffn_down.weight	0xe3ddf720	0x3b80000
145	blk.15.ffn_gate.weight	0xe795f720	0x2df0000
146	blk.15.ffn_norm.weight	0xea74f720	0x4000
147	blk.15.ffn_up.weight	0xea753720	0x2df0000
148	blk.16.attn_k.weight	0xed543720	0x440000
149	blk.16.attn_norm.weight	0xed983720	0x4000
150	blk.16.attn_output.weight	0xed987720	0x1100000
151	blk.16.attn_q.weight	0xeea87720	0x1100000
152	blk.16.attn_v.weight	0xefb87720	0x800000
153	blk.16.ffn_down.weight	0xf0387720	0x3b80000
154	blk.16.ffn_gate.weight	0xf3f07720	0x3b80000
155	blk.16.ffn_norm.weight	0xf7a87720	0x4000
156	blk.16.ffn_up.weight	0xf7a8b720	0x3b80000
157	blk.17.attn_k.weight	0xfb60b720	0x348000
158	blk.17.attn_norm.weight	0xfb953720	0x4000
159	blk.17.attn_output.weight	0xfb957720	0x1100000
160	blk.17.attn_q.weight	0xfca57720	0xd20000
161	blk.17.attn_v.weight	0xfd777720	0x440000
162	blk.17.ffn_down.weight	0xfdbb7720	0x3b80000
163	blk.17.ffn_gate.weight	0x101737720	0x3b80000
164	blk.17.ffn_norm.weight	0x1052b7720	0x4000
165	blk.17.ffn_up.weight	0x1052bb720	0x3b80000
166	blk.18.attn_k.weight	0x108e3b720	0x440000
167	blk.18.attn_norm.weight	0x10927b720	0x4000
168	blk.18.attn_output.weight	0x10927f720	0x1100000
169	blk.18.attn_q.weight	0x10a37f720	0x1100000
170	blk.18.attn_v.weight	0x10b47f720	0x800000
171	blk.18.ffn_down.weight	0x10bc7f720	0x3b80000
172	blk.18.ffn_gate.weight	0x10f7ff720	0x3b80000
173	blk.18.ffn_norm.weight	0x11337f720	0x4000
174	blk.18.ffn_up.weight	0x113383720	0x3b80000
175	blk.19.attn_k.weight	0x116f03720	0x440000
176	blk.19.attn_norm.weight	0x117343720	0x4000
177	blk.19.attn_output.weight	0x117347720	0x1100000
178	blk.19.attn_q.weight	0x118447720	0x1100000
179	blk.19.attn_v.weight	0x119547720	0x800000
180	blk.19.ffn_down.weight	0x119d47720	0x3b80000
181	blk.19.ffn_gate.weight	0x11d8c7720	0x3b80000
182	blk.19.ffn_norm.weight	0x121447720	0x4000
183	blk.19.ffn_up.weight	0x12144b720	0x3b80000
184	blk.20.attn_k.weight	0x124fcb720	0x440000
185	blk.20.attn_norm.weight	0x12540b720	0x4000
186	blk.20.attn_output.weight	0x12540f720	0x1100000
187	blk.20.attn_q.weight	0x12650f720	0x1100000
188	blk.20.attn_v.weight	0x12760f720	0x800000
189	blk.20.ffn_down.weight	0x127e0f720	0x3b80000
190	blk.20.ffn_gate.weight	0x12b98f720	0x3b80000
191	blk.20.ffn_norm.weight	0x12f50f720	0x4000
192	blk.20.ffn_up.weight	0x12f513720	0x3b80000
193	blk.21.attn_k.weight	0x133093720	0x440000
194	blk.21.attn_norm.weight	0x1334d3720	0x4000
195	blk.21.attn_output.weight	0x1334d7720	0x1100000
196	blk.21.attn_q.weight	0x1345d7720	0x1100000
197	blk.21.attn_v.weight	0x1356d7720	0x800000
198	blk.21.ffn_down.weight	0x135ed7720	0x3b80000
199	blk.21.ffn_gate.weight	0x139a57720	0x3b80000
200	blk.21.ffn_norm.weight	0x13d5d7720	0x4000
201	blk.21.ffn_up.weight	0x13d5db720	0x3b80000
202	blk.22.attn_k.weight	0x14115b720	0x440000
203	blk.22.attn_norm.weight	0x14159b720	0x4000
204	blk.22.attn_output.weight	0x14159f720	0x1100000
205	blk.22.attn_q.weight	0x14269f720	0x1100000
206	blk.22.attn_v.weight	0x14379f720	0x800000
207	blk.22.ffn_down.weight	0x143f9f720	0x3b80000
208	blk.22.ffn_gate.weight	0x147b1f720	0x3b80000
209	blk.22.ffn_norm.weight	0x14b69f720	0x4000
210	blk.22.ffn_up.weight	0x14b6a3720	0x3b80000
211	blk.23.attn_k.weight	0x14f223720	0x440000
212	blk.23.attn_norm.weight	0x14f663720	0x4000
213	blk.23.attn_output.weight	0x14f667720	0x1100000
214	blk.23.attn_q.weight	0x150767720	0x1100000
215	blk.23.attn_v.weight	0x151867720	0x800000
216	blk.23.ffn_down.weight	0x152067720	0x3b80000
217	blk.23.ffn_gate.weight	0x155be7720	0x3b80000
218	blk.23.ffn_norm.weight	0x159767720	0x4000
219	blk.23.ffn_up.weight	0x15976b720	0x3b80000
220	blk.24.attn_k.weight	0x15d2eb720	0x440000
221	blk.24.attn_norm.weight	0x15d72b720	0x4000
222	blk.24.attn_output.weight	0x15d72f720	0x1100000
223	blk.24.attn_q.weight	0x15e82f720	0x1100000
224	blk.24.attn_v.weight	0x15f92f720	0x800000
225	blk.24.ffn_down.weight	0x16012f720	0x3b80000
226	blk.24.ffn_gate.weight	0x163caf720	0x3b80000
227	blk.24.ffn_norm.weight	0x16782f720	0x4000
228	blk.24.ffn_up.weight	0x167833720	0x3b80000
229	blk.25.attn_k.weight	0x16b3b3720	0x440000
230	blk.25.attn_norm.weight	0x16b7f3720	0x4000
231	blk.25.attn_output.weight	0x16b7f7720	0x1100000
232	blk.25.attn_q.weight	0x16c8f7720	0x1100000
233	blk.25.attn_v.weight	0x16d9f7720	0x800000
234	blk.25.ffn_down.weight	0x16e1f7720	0x3b80000
235	blk.25.ffn_gate.weight	0x171d77720	0x3b80000
236	blk.25.ffn_norm.weight	0x1758f7720	0x4000
237	blk.25.ffn_up.weight	0x1758fb720	0x3b80000
238	blk.26.attn_k.weight	0x17947b720	0x440000
239	blk.26.attn_norm.weight	0x1798bb720	0x4000
240	blk.26.attn_output.weight	0x1798bf720	0x1100000
241	blk.26.attn_q.weight	0x17a9bf720	0x1100000
242	blk.26.attn_v.weight	0x17babf720	0x800000
243	blk.26.ffn_down.weight	0x17c2bf720	0x3b80000
244	blk.26.ffn_gate.weight	0x17fe3f720	0x3b80000
245	blk.26.ffn_norm.weight	0x1839bf720	0x4000
246	blk.26.ffn_up.weight	0x1839c3720	0x3b80000
247	blk.27.attn_k.weight	0x187543720	0x440000
248	blk.27.attn_norm.weight	0x187983720	0x4000
249	blk.27.attn_output.weight	0x187987720	0x1100000
250	blk.27.attn_q.weight	0x188a87720	0x1100000
251	blk.27.attn_v.weight	0x189b87720	0x800000
252	blk.27.ffn_down.weight	0x18a387720	0x3b80000
253	blk.27.ffn_gate.weight	0x18df07720	0x3b80000
254	blk.27.ffn_norm.weight	0x191a87720	0x4000
255	blk.27.ffn_up.weight	0x191a8b720	0x3b80000
256	blk.28.attn_k.weight	0x19560b720	0x440000
257	blk.28.attn_norm.weight	0x195a4b720	0x4000
258	blk.28.attn_output.weight	0x195a4f720	0x1100000
259	blk.28.attn_q.weight	0x196b4f720	0x1100000
260	blk.28.attn_v.weight	0x197c4f720	0x800000
261	blk.28.ffn_down.weight	0x19844f720	0x3b80000
262	blk.28.ffn_gate.weight	0x19bfcf720	0x3b80000
263	blk.28.ffn_norm.weight	0x19fb4f720	0x4000
264	blk.28.ffn_up.weight	0x19fb53720	0x3b80000
265	blk.29.attn_k.weight	0x1a36d3720	0x440000
266	blk.29.attn_norm.weight	0x1a3b13720	0x4000
267	blk.29.attn_output.weight	0x1a3b17720	0x1100000
268	blk.29.attn_q.weight	0x1a4c17720	0x1100000
269	blk.29.attn_v.weight	0x1a5d17720	0x800000
270	blk.29.ffn_down.weight	0x1a6517720	0x3b80000
271	blk.29.ffn_gate.weight	0x1aa097720	0x3b80000
272	blk.29.ffn_norm.weight	0x1adc17720	0x4000
273	blk.29.ffn_up.weight	0x1adc1b720	0x3b80000
274	blk.30.attn_k.weight	0x1b179b720	0x440000
275	blk.30.attn_norm.weight	0x1b1bdb720	0x4000
276	blk.30.attn_output.weight	0x1b1bdf720	0x1100000
277	blk.30.attn_q.weight	0x1b2cdf720	0x1100000
278	blk.30.attn_v.weight	0x1b3ddf720	0x800000
279	blk.30.ffn_down.weight	0x1b45df720	0x3b80000
280	blk.30.ffn_gate.weight	0x1b815f720	0x3b80000
281	blk.30.ffn_norm.weight	0x1bbcdf720	0x4000
282	blk.30.ffn_up.weight	0x1bbce3720	0x3b80000
283	blk.31.attn_k.weight	0x1bf863720	0x348000
284	blk.31.attn_norm.weight	0x1bfbab720	0x4000
285	blk.31.attn_output.weight	0x1bfbaf720	0x1100000
286	blk.31.attn_q.weight	0x1c0caf720	0xd20000
287	blk.31.attn_v.weight	0x1c19cf720	0x440000
288	blk.31.ffn_down.weight	0x1c1e0f720	0x3b80000
289	blk.31.ffn_gate.weight	0x1c598f720	0x3b80000
290	blk.31.ffn_norm.weight	0x1c950f720	0x4000
291	blk.31.ffn_up.weight	0x1c9513720	0x3b80000

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	Q8_0
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	Q6_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	Q8_0
7	blk.0.attn_q.weight	Block 0 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
8	blk.0.attn_v.weight	Block 0 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
16	blk.1.attn_q.weight	Block 1 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
17	blk.1.attn_v.weight	Block 1 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
25	blk.2.attn_q.weight	Block 2 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
26	blk.2.attn_v.weight	Block 2 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
34	blk.3.attn_q.weight	Block 3 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
35	blk.3.attn_v.weight	Block 3 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
43	blk.4.attn_q.weight	Block 4 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
44	blk.4.attn_v.weight	Block 4 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
52	blk.5.attn_q.weight	Block 5 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
53	blk.5.attn_v.weight	Block 5 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
61	blk.6.attn_q.weight	Block 6 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
62	blk.6.attn_v.weight	Block 6 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
70	blk.7.attn_q.weight	Block 7 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
71	blk.7.attn_v.weight	Block 7 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
79	blk.8.attn_q.weight	Block 8 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
80	blk.8.attn_v.weight	Block 8 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
88	blk.9.attn_q.weight	Block 9 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
89	blk.9.attn_v.weight	Block 9 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
97	blk.10.attn_q.weight	Block 10 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
98	blk.10.attn_v.weight	Block 10 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
106	blk.11.attn_q.weight	Block 11 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
107	blk.11.attn_v.weight	Block 11 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q6_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	Q8_0
115	blk.12.attn_q.weight	Block 12 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
116	blk.12.attn_v.weight	Block 12 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q8_0
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	Q8_0
124	blk.13.attn_q.weight	Block 13 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
125	blk.13.attn_v.weight	Block 13 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q6_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	Q6_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	Q8_0
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	Q8_0
133	blk.14.attn_q.weight	Block 14 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
134	blk.14.attn_v.weight	Block 14 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q6_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	Q6_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	Q6_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	Q8_0
142	blk.15.attn_q.weight	Block 15 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
143	blk.15.attn_v.weight	Block 15 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q6_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	Q6_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	Q8_0
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	Q8_0
151	blk.16.attn_q.weight	Block 16 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
152	blk.16.attn_v.weight	Block 16 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q6_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	Q8_0
160	blk.17.attn_q.weight	Block 17 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
161	blk.17.attn_v.weight	Block 17 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
169	blk.18.attn_q.weight	Block 18 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
170	blk.18.attn_v.weight	Block 18 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
178	blk.19.attn_q.weight	Block 19 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
179	blk.19.attn_v.weight	Block 19 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
187	blk.20.attn_q.weight	Block 20 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
188	blk.20.attn_v.weight	Block 20 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
196	blk.21.attn_q.weight	Block 21 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
197	blk.21.attn_v.weight	Block 21 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
205	blk.22.attn_q.weight	Block 22 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
206	blk.22.attn_v.weight	Block 22 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
214	blk.23.attn_q.weight	Block 23 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
215	blk.23.attn_v.weight	Block 23 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
223	blk.24.attn_q.weight	Block 24 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
224	blk.24.attn_v.weight	Block 24 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
232	blk.25.attn_q.weight	Block 25 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
233	blk.25.attn_v.weight	Block 25 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
241	blk.26.attn_q.weight	Block 26 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
242	blk.26.attn_v.weight	Block 26 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
250	blk.27.attn_q.weight	Block 27 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
251	blk.27.attn_v.weight	Block 27 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
259	blk.28.attn_q.weight	Block 28 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
260	blk.28.attn_v.weight	Block 28 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
268	blk.29.attn_q.weight	Block 29 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
269	blk.29.attn_v.weight	Block 29 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q8_0
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	Q8_0
277	blk.30.attn_q.weight	Block 30 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q8_0
278	blk.30.attn_v.weight	Block 30 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
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	Q8_0
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	Q8_0

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	Q6_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	Q8_0
286	blk.31.attn_q.weight	Block 31 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	Q6_K
287	blk.31.attn_v.weight	Block 31 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	Q8_0
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	Q8_0
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	Q8_0

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

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Watt-Tool-8B-Q8_0.gguf - GGUF Internal File Dump

Key Value Metadata Store

Tensors Overview ~8B Elements

Tensor Data Offset

83 KiB

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