Dolphin-Mistral-24B-Venice-Edition-pruned-GGUF/scores/Dolphin-Mistral-24B-Venice-Edition-Q6_K.md

Dolphin-Mistral-24B-Venice-Edition-pruned-Q6_K.gguf - GGUF Internal File Dump

• Endian: LITTLE endian

Key Value Metadata Store

There are 46 key-value pairs in this file

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

Tensors Overview ~22B Elements

Total number of elements in all tensors: 22460892160 Elements

• Dolphin-Mistral-24B-Venice-Edition-pruned-Q6_K.gguf - GGUF Internal File Dump
  • Key Value Metadata Store
  • Tensors Overview ~22B Elements
    • Tensor Data Offset
    • Base Tensor Group : ~1B Elements
    • Block 0 Tensor Group : ~556M Elements
    • Block 1 Tensor Group : ~556M Elements
    • Block 2 Tensor Group : ~556M Elements
    • Block 3 Tensor Group : ~556M Elements
    • Block 4 Tensor Group : ~556M Elements
    • Block 5 Tensor Group : ~556M Elements
    • Block 6 Tensor Group : ~556M Elements
    • Block 7 Tensor Group : ~556M Elements
    • Block 8 Tensor Group : ~556M Elements
    • Block 9 Tensor Group : ~556M Elements
    • Block 10 Tensor Group : ~556M Elements
    • Block 11 Tensor Group : ~556M Elements
    • Block 12 Tensor Group : ~556M Elements
    • Block 13 Tensor Group : ~556M Elements
    • Block 14 Tensor Group : ~556M Elements
    • Block 15 Tensor Group : ~556M Elements
    • Block 16 Tensor Group : ~556M Elements
    • Block 17 Tensor Group : ~556M Elements
    • Block 18 Tensor Group : ~556M Elements
    • Block 19 Tensor Group : ~556M Elements
    • Block 20 Tensor Group : ~556M Elements
    • Block 21 Tensor Group : ~556M Elements
    • Block 22 Tensor Group : ~556M Elements
    • Block 23 Tensor Group : ~556M Elements
    • Block 24 Tensor Group : ~556M Elements
    • Block 25 Tensor Group : ~556M Elements
    • Block 26 Tensor Group : ~556M Elements
    • Block 27 Tensor Group : ~556M Elements
    • Block 28 Tensor Group : ~556M Elements
    • Block 29 Tensor Group : ~556M Elements
    • Block 30 Tensor Group : ~556M Elements
    • Block 31 Tensor Group : ~556M Elements
    • Block 32 Tensor Group : ~556M Elements
    • Block 33 Tensor Group : ~556M Elements
    • Block 34 Tensor Group : ~556M Elements
    • Block 35 Tensor Group : ~556M Elements
    • Block 36 Tensor Group : ~556M Elements
    • Block 37 Tensor Group : ~556M Elements

Tensor Data Offset

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

T_ID	Tensor Layer Name	Data Offset (B)	Data Size (B)
0	output.weight	0x784500	0x20d00000
1	output_norm.weight	0x21484500	0x5000
2	token_embd.weight	0x21489500	0x11300000
3	blk.0.attn_k.weight	0x32789500	0x370000
4	blk.0.attn_norm.weight	0x32af9500	0x5000
5	blk.0.attn_output.weight	0x32afe500	0x1068000
6	blk.0.attn_q.weight	0x33b66500	0xdc0000
7	blk.0.attn_v.weight	0x34926500	0x550000
8	blk.0.ffn_down.weight	0x34e76500	0x8340000
9	blk.0.ffn_gate.weight	0x3d1b6500	0x6e00000
10	blk.0.ffn_norm.weight	0x43fb6500	0x5000
11	blk.0.ffn_up.weight	0x43fbb500	0x6e00000
12	blk.1.attn_k.weight	0x4adbb500	0x370000
13	blk.1.attn_norm.weight	0x4b12b500	0x5000
14	blk.1.attn_output.weight	0x4b130500	0x1068000
15	blk.1.attn_q.weight	0x4c198500	0xdc0000
16	blk.1.attn_v.weight	0x4cf58500	0x550000
17	blk.1.ffn_down.weight	0x4d4a8500	0x8340000
18	blk.1.ffn_gate.weight	0x557e8500	0x6e00000
19	blk.1.ffn_norm.weight	0x5c5e8500	0x5000
20	blk.1.ffn_up.weight	0x5c5ed500	0x6e00000
21	blk.2.attn_k.weight	0x633ed500	0x370000
22	blk.2.attn_norm.weight	0x6375d500	0x5000
23	blk.2.attn_output.weight	0x63762500	0x1068000
24	blk.2.attn_q.weight	0x647ca500	0xdc0000
25	blk.2.attn_v.weight	0x6558a500	0x550000
26	blk.2.ffn_down.weight	0x65ada500	0x8340000
27	blk.2.ffn_gate.weight	0x6de1a500	0x6e00000
28	blk.2.ffn_norm.weight	0x74c1a500	0x5000
29	blk.2.ffn_up.weight	0x74c1f500	0x6e00000
30	blk.3.attn_k.weight	0x7ba1f500	0x370000
31	blk.3.attn_norm.weight	0x7bd8f500	0x5000
32	blk.3.attn_output.weight	0x7bd94500	0x1068000
33	blk.3.attn_q.weight	0x7cdfc500	0xdc0000
34	blk.3.attn_v.weight	0x7dbbc500	0x550000
35	blk.3.ffn_down.weight	0x7e10c500	0x8340000
36	blk.3.ffn_gate.weight	0x8644c500	0x6e00000
37	blk.3.ffn_norm.weight	0x8d24c500	0x5000
38	blk.3.ffn_up.weight	0x8d251500	0x6e00000
39	blk.4.attn_k.weight	0x94051500	0x370000
40	blk.4.attn_norm.weight	0x943c1500	0x5000
41	blk.4.attn_output.weight	0x943c6500	0x1068000
42	blk.4.attn_q.weight	0x9542e500	0xdc0000
43	blk.4.attn_v.weight	0x961ee500	0x550000
44	blk.4.ffn_down.weight	0x9673e500	0x8340000
45	blk.4.ffn_gate.weight	0x9ea7e500	0x6e00000
46	blk.4.ffn_norm.weight	0xa587e500	0x5000
47	blk.4.ffn_up.weight	0xa5883500	0x6e00000
48	blk.5.attn_k.weight	0xac683500	0x370000
49	blk.5.attn_norm.weight	0xac9f3500	0x5000
50	blk.5.attn_output.weight	0xac9f8500	0x1068000
51	blk.5.attn_q.weight	0xada60500	0xdc0000
52	blk.5.attn_v.weight	0xae820500	0x550000
53	blk.5.ffn_down.weight	0xaed70500	0x8340000
54	blk.5.ffn_gate.weight	0xb70b0500	0x6e00000
55	blk.5.ffn_norm.weight	0xbdeb0500	0x5000
56	blk.5.ffn_up.weight	0xbdeb5500	0x6e00000
57	blk.6.attn_k.weight	0xc4cb5500	0x370000
58	blk.6.attn_norm.weight	0xc5025500	0x5000
59	blk.6.attn_output.weight	0xc502a500	0x1068000
60	blk.6.attn_q.weight	0xc6092500	0xdc0000
61	blk.6.attn_v.weight	0xc6e52500	0x550000
62	blk.6.ffn_down.weight	0xc73a2500	0x8340000
63	blk.6.ffn_gate.weight	0xcf6e2500	0x6e00000
64	blk.6.ffn_norm.weight	0xd64e2500	0x5000
65	blk.6.ffn_up.weight	0xd64e7500	0x6e00000
66	blk.7.attn_k.weight	0xdd2e7500	0x370000
67	blk.7.attn_norm.weight	0xdd657500	0x5000
68	blk.7.attn_output.weight	0xdd65c500	0x1068000
69	blk.7.attn_q.weight	0xde6c4500	0xdc0000
70	blk.7.attn_v.weight	0xdf484500	0x550000
71	blk.7.ffn_down.weight	0xdf9d4500	0x8340000
72	blk.7.ffn_gate.weight	0xe7d14500	0x6e00000
73	blk.7.ffn_norm.weight	0xeeb14500	0x5000
74	blk.7.ffn_up.weight	0xeeb19500	0x6e00000
75	blk.8.attn_k.weight	0xf5919500	0x370000
76	blk.8.attn_norm.weight	0xf5c89500	0x5000
77	blk.8.attn_output.weight	0xf5c8e500	0x1068000
78	blk.8.attn_q.weight	0xf6cf6500	0xdc0000
79	blk.8.attn_v.weight	0xf7ab6500	0x550000
80	blk.8.ffn_down.weight	0xf8006500	0x8340000
81	blk.8.ffn_gate.weight	0x100346500	0x6e00000
82	blk.8.ffn_norm.weight	0x107146500	0x5000
83	blk.8.ffn_up.weight	0x10714b500	0x6e00000
84	blk.9.attn_k.weight	0x10df4b500	0x370000
85	blk.9.attn_norm.weight	0x10e2bb500	0x5000
86	blk.9.attn_output.weight	0x10e2c0500	0x1068000
87	blk.9.attn_q.weight	0x10f328500	0xdc0000
88	blk.9.attn_v.weight	0x1100e8500	0x550000
89	blk.9.ffn_down.weight	0x110638500	0x8340000
90	blk.9.ffn_gate.weight	0x118978500	0x6e00000
91	blk.9.ffn_norm.weight	0x11f778500	0x5000
92	blk.9.ffn_up.weight	0x11f77d500	0x6e00000
93	blk.10.attn_k.weight	0x12657d500	0x370000
94	blk.10.attn_norm.weight	0x1268ed500	0x5000
95	blk.10.attn_output.weight	0x1268f2500	0x1068000
96	blk.10.attn_q.weight	0x12795a500	0xdc0000
97	blk.10.attn_v.weight	0x12871a500	0x550000
98	blk.10.ffn_down.weight	0x128c6a500	0x8340000
99	blk.10.ffn_gate.weight	0x130faa500	0x6e00000
100	blk.10.ffn_norm.weight	0x137daa500	0x5000
101	blk.10.ffn_up.weight	0x137daf500	0x6e00000
102	blk.11.attn_k.weight	0x13ebaf500	0x370000
103	blk.11.attn_norm.weight	0x13ef1f500	0x5000
104	blk.11.attn_output.weight	0x13ef24500	0x1068000
105	blk.11.attn_q.weight	0x13ff8c500	0xdc0000
106	blk.11.attn_v.weight	0x140d4c500	0x550000
107	blk.11.ffn_down.weight	0x14129c500	0x8340000
108	blk.11.ffn_gate.weight	0x1495dc500	0x6e00000
109	blk.11.ffn_norm.weight	0x1503dc500	0x5000
110	blk.11.ffn_up.weight	0x1503e1500	0x6e00000
111	blk.12.attn_k.weight	0x1571e1500	0x370000
112	blk.12.attn_norm.weight	0x157551500	0x5000
113	blk.12.attn_output.weight	0x157556500	0x1068000
114	blk.12.attn_q.weight	0x1585be500	0xdc0000
115	blk.12.attn_v.weight	0x15937e500	0x550000
116	blk.12.ffn_down.weight	0x1598ce500	0x8340000
117	blk.12.ffn_gate.weight	0x161c0e500	0x6e00000
118	blk.12.ffn_norm.weight	0x168a0e500	0x5000
119	blk.12.ffn_up.weight	0x168a13500	0x6e00000
120	blk.13.attn_k.weight	0x16f813500	0x370000
121	blk.13.attn_norm.weight	0x16fb83500	0x5000
122	blk.13.attn_output.weight	0x16fb88500	0x1068000
123	blk.13.attn_q.weight	0x170bf0500	0xdc0000
124	blk.13.attn_v.weight	0x1719b0500	0x550000
125	blk.13.ffn_down.weight	0x171f00500	0x8340000
126	blk.13.ffn_gate.weight	0x17a240500	0x6e00000
127	blk.13.ffn_norm.weight	0x181040500	0x5000
128	blk.13.ffn_up.weight	0x181045500	0x6e00000
129	blk.14.attn_k.weight	0x187e45500	0x370000
130	blk.14.attn_norm.weight	0x1881b5500	0x5000
131	blk.14.attn_output.weight	0x1881ba500	0x1068000
132	blk.14.attn_q.weight	0x189222500	0xdc0000
133	blk.14.attn_v.weight	0x189fe2500	0x550000
134	blk.14.ffn_down.weight	0x18a532500	0x8340000
135	blk.14.ffn_gate.weight	0x192872500	0x6e00000
136	blk.14.ffn_norm.weight	0x199672500	0x5000
137	blk.14.ffn_up.weight	0x199677500	0x6e00000
138	blk.15.attn_k.weight	0x1a0477500	0x370000
139	blk.15.attn_norm.weight	0x1a07e7500	0x5000
140	blk.15.attn_output.weight	0x1a07ec500	0x1068000
141	blk.15.attn_q.weight	0x1a1854500	0xdc0000
142	blk.15.attn_v.weight	0x1a2614500	0x550000
143	blk.15.ffn_down.weight	0x1a2b64500	0x8340000
144	blk.15.ffn_gate.weight	0x1aaea4500	0x6e00000
145	blk.15.ffn_norm.weight	0x1b1ca4500	0x5000
146	blk.15.ffn_up.weight	0x1b1ca9500	0x6e00000
147	blk.16.attn_k.weight	0x1b8aa9500	0x370000
148	blk.16.attn_norm.weight	0x1b8e19500	0x5000
149	blk.16.attn_output.weight	0x1b8e1e500	0x1068000
150	blk.16.attn_q.weight	0x1b9e86500	0xdc0000
151	blk.16.attn_v.weight	0x1bac46500	0x550000
152	blk.16.ffn_down.weight	0x1bb196500	0x8340000
153	blk.16.ffn_gate.weight	0x1c34d6500	0x6e00000
154	blk.16.ffn_norm.weight	0x1ca2d6500	0x5000
155	blk.16.ffn_up.weight	0x1ca2db500	0x6e00000
156	blk.17.attn_k.weight	0x1d10db500	0x370000
157	blk.17.attn_norm.weight	0x1d144b500	0x5000
158	blk.17.attn_output.weight	0x1d1450500	0x1068000
159	blk.17.attn_q.weight	0x1d24b8500	0xdc0000
160	blk.17.attn_v.weight	0x1d3278500	0x550000
161	blk.17.ffn_down.weight	0x1d37c8500	0x8340000
162	blk.17.ffn_gate.weight	0x1dbb08500	0x6e00000
163	blk.17.ffn_norm.weight	0x1e2908500	0x5000
164	blk.17.ffn_up.weight	0x1e290d500	0x6e00000
165	blk.18.attn_k.weight	0x1e970d500	0x370000
166	blk.18.attn_norm.weight	0x1e9a7d500	0x5000
167	blk.18.attn_output.weight	0x1e9a82500	0x1068000
168	blk.18.attn_q.weight	0x1eaaea500	0xdc0000
169	blk.18.attn_v.weight	0x1eb8aa500	0x550000
170	blk.18.ffn_down.weight	0x1ebdfa500	0x8340000
171	blk.18.ffn_gate.weight	0x1f413a500	0x6e00000
172	blk.18.ffn_norm.weight	0x1faf3a500	0x5000
173	blk.18.ffn_up.weight	0x1faf3f500	0x6e00000
174	blk.19.attn_k.weight	0x201d3f500	0x370000
175	blk.19.attn_norm.weight	0x2020af500	0x5000
176	blk.19.attn_output.weight	0x2020b4500	0x1068000
177	blk.19.attn_q.weight	0x20311c500	0xdc0000
178	blk.19.attn_v.weight	0x203edc500	0x550000
179	blk.19.ffn_down.weight	0x20442c500	0x8340000
180	blk.19.ffn_gate.weight	0x20c76c500	0x6e00000
181	blk.19.ffn_norm.weight	0x21356c500	0x5000
182	blk.19.ffn_up.weight	0x213571500	0x6e00000
183	blk.20.attn_k.weight	0x21a371500	0x370000
184	blk.20.attn_norm.weight	0x21a6e1500	0x5000
185	blk.20.attn_output.weight	0x21a6e6500	0x1068000
186	blk.20.attn_q.weight	0x21b74e500	0xdc0000
187	blk.20.attn_v.weight	0x21c50e500	0x550000
188	blk.20.ffn_down.weight	0x21ca5e500	0x8340000
189	blk.20.ffn_gate.weight	0x224d9e500	0x6e00000
190	blk.20.ffn_norm.weight	0x22bb9e500	0x5000
191	blk.20.ffn_up.weight	0x22bba3500	0x6e00000
192	blk.21.attn_k.weight	0x2329a3500	0x370000
193	blk.21.attn_norm.weight	0x232d13500	0x5000
194	blk.21.attn_output.weight	0x232d18500	0x1068000
195	blk.21.attn_q.weight	0x233d80500	0xdc0000
196	blk.21.attn_v.weight	0x234b40500	0x550000
197	blk.21.ffn_down.weight	0x235090500	0x8340000
198	blk.21.ffn_gate.weight	0x23d3d0500	0x6e00000
199	blk.21.ffn_norm.weight	0x2441d0500	0x5000
200	blk.21.ffn_up.weight	0x2441d5500	0x6e00000
201	blk.22.attn_k.weight	0x24afd5500	0x370000
202	blk.22.attn_norm.weight	0x24b345500	0x5000
203	blk.22.attn_output.weight	0x24b34a500	0x1068000
204	blk.22.attn_q.weight	0x24c3b2500	0xdc0000
205	blk.22.attn_v.weight	0x24d172500	0x550000
206	blk.22.ffn_down.weight	0x24d6c2500	0x8340000
207	blk.22.ffn_gate.weight	0x255a02500	0x6e00000
208	blk.22.ffn_norm.weight	0x25c802500	0x5000
209	blk.22.ffn_up.weight	0x25c807500	0x6e00000
210	blk.23.attn_k.weight	0x263607500	0x370000
211	blk.23.attn_norm.weight	0x263977500	0x5000
212	blk.23.attn_output.weight	0x26397c500	0x1068000
213	blk.23.attn_q.weight	0x2649e4500	0xdc0000
214	blk.23.attn_v.weight	0x2657a4500	0x550000
215	blk.23.ffn_down.weight	0x265cf4500	0x8340000
216	blk.23.ffn_gate.weight	0x26e034500	0x6e00000
217	blk.23.ffn_norm.weight	0x274e34500	0x5000
218	blk.23.ffn_up.weight	0x274e39500	0x6e00000
219	blk.24.attn_k.weight	0x27bc39500	0x370000
220	blk.24.attn_norm.weight	0x27bfa9500	0x5000
221	blk.24.attn_output.weight	0x27bfae500	0x1068000
222	blk.24.attn_q.weight	0x27d016500	0xdc0000
223	blk.24.attn_v.weight	0x27ddd6500	0x550000
224	blk.24.ffn_down.weight	0x27e326500	0x8340000
225	blk.24.ffn_gate.weight	0x286666500	0x6e00000
226	blk.24.ffn_norm.weight	0x28d466500	0x5000
227	blk.24.ffn_up.weight	0x28d46b500	0x6e00000
228	blk.25.attn_k.weight	0x29426b500	0x41a000
229	blk.25.attn_norm.weight	0x294685500	0x5000
230	blk.25.attn_output.weight	0x29468a500	0x1068000
231	blk.25.attn_q.weight	0x2956f2500	0x1068000
232	blk.25.attn_v.weight	0x29675a500	0x550000
233	blk.25.ffn_down.weight	0x296caa500	0x8340000
234	blk.25.ffn_gate.weight	0x29efea500	0x6e00000
235	blk.25.ffn_norm.weight	0x2a5dea500	0x5000
236	blk.25.ffn_up.weight	0x2a5def500	0x6e00000
237	blk.26.attn_k.weight	0x2acbef500	0x370000
238	blk.26.attn_norm.weight	0x2acf5f500	0x5000
239	blk.26.attn_output.weight	0x2acf64500	0x1068000
240	blk.26.attn_q.weight	0x2adfcc500	0xdc0000
241	blk.26.attn_v.weight	0x2aed8c500	0x550000
242	blk.26.ffn_down.weight	0x2af2dc500	0x8340000
243	blk.26.ffn_gate.weight	0x2b761c500	0x6e00000
244	blk.26.ffn_norm.weight	0x2be41c500	0x5000
245	blk.26.ffn_up.weight	0x2be421500	0x6e00000
246	blk.27.attn_k.weight	0x2c5221500	0x370000
247	blk.27.attn_norm.weight	0x2c5591500	0x5000
248	blk.27.attn_output.weight	0x2c5596500	0x1068000
249	blk.27.attn_q.weight	0x2c65fe500	0xdc0000
250	blk.27.attn_v.weight	0x2c73be500	0x550000
251	blk.27.ffn_down.weight	0x2c790e500	0x8340000
252	blk.27.ffn_gate.weight	0x2cfc4e500	0x6e00000
253	blk.27.ffn_norm.weight	0x2d6a4e500	0x5000
254	blk.27.ffn_up.weight	0x2d6a53500	0x6e00000
255	blk.28.attn_k.weight	0x2dd853500	0x41a000
256	blk.28.attn_norm.weight	0x2ddc6d500	0x5000
257	blk.28.attn_output.weight	0x2ddc72500	0x1068000
258	blk.28.attn_q.weight	0x2decda500	0x1068000
259	blk.28.attn_v.weight	0x2dfd42500	0x550000
260	blk.28.ffn_down.weight	0x2e0292500	0x8340000
261	blk.28.ffn_gate.weight	0x2e85d2500	0x6e00000
262	blk.28.ffn_norm.weight	0x2ef3d2500	0x5000
263	blk.28.ffn_up.weight	0x2ef3d7500	0x6e00000
264	blk.29.attn_k.weight	0x2f61d7500	0x370000
265	blk.29.attn_norm.weight	0x2f6547500	0x5000
266	blk.29.attn_output.weight	0x2f654c500	0x1068000
267	blk.29.attn_q.weight	0x2f75b4500	0xdc0000
268	blk.29.attn_v.weight	0x2f8374500	0x550000
269	blk.29.ffn_down.weight	0x2f88c4500	0x8340000
270	blk.29.ffn_gate.weight	0x300c04500	0x6e00000
271	blk.29.ffn_norm.weight	0x307a04500	0x5000
272	blk.29.ffn_up.weight	0x307a09500	0x6e00000
273	blk.30.attn_k.weight	0x30e809500	0x41a000
274	blk.30.attn_norm.weight	0x30ec23500	0x5000
275	blk.30.attn_output.weight	0x30ec28500	0x1068000
276	blk.30.attn_q.weight	0x30fc90500	0x1068000
277	blk.30.attn_v.weight	0x310cf8500	0x550000
278	blk.30.ffn_down.weight	0x311248500	0x8340000
279	blk.30.ffn_gate.weight	0x319588500	0x8340000
280	blk.30.ffn_norm.weight	0x3218c8500	0x5000
281	blk.30.ffn_up.weight	0x3218cd500	0x8340000
282	blk.31.attn_k.weight	0x329c0d500	0x370000
283	blk.31.attn_norm.weight	0x329f7d500	0x5000
284	blk.31.attn_output.weight	0x329f82500	0x1068000
285	blk.31.attn_q.weight	0x32afea500	0xdc0000
286	blk.31.attn_v.weight	0x32bdaa500	0x550000
287	blk.31.ffn_down.weight	0x32c2fa500	0x8340000
288	blk.31.ffn_gate.weight	0x33463a500	0x8340000
289	blk.31.ffn_norm.weight	0x33c97a500	0x5000
290	blk.31.ffn_up.weight	0x33c97f500	0x8340000
291	blk.32.attn_k.weight	0x344cbf500	0x41a000
292	blk.32.attn_norm.weight	0x3450d9500	0x5000
293	blk.32.attn_output.weight	0x3450de500	0x1068000
294	blk.32.attn_q.weight	0x346146500	0x1068000
295	blk.32.attn_v.weight	0x3471ae500	0x550000
296	blk.32.ffn_down.weight	0x3476fe500	0x8340000
297	blk.32.ffn_gate.weight	0x34fa3e500	0x8340000
298	blk.32.ffn_norm.weight	0x357d7e500	0x5000
299	blk.32.ffn_up.weight	0x357d83500	0x8340000
300	blk.33.attn_k.weight	0x3600c3500	0x41a000
301	blk.33.attn_norm.weight	0x3604dd500	0x5000
302	blk.33.attn_output.weight	0x3604e2500	0x1068000
303	blk.33.attn_q.weight	0x36154a500	0x1068000
304	blk.33.attn_v.weight	0x3625b2500	0x550000
305	blk.33.ffn_down.weight	0x362b02500	0x8340000
306	blk.33.ffn_gate.weight	0x36ae42500	0x8340000
307	blk.33.ffn_norm.weight	0x373182500	0x5000
308	blk.33.ffn_up.weight	0x373187500	0x8340000
309	blk.34.attn_k.weight	0x37b4c7500	0x41a000
310	blk.34.attn_norm.weight	0x37b8e1500	0x5000
311	blk.34.attn_output.weight	0x37b8e6500	0x1068000
312	blk.34.attn_q.weight	0x37c94e500	0x1068000
313	blk.34.attn_v.weight	0x37d9b6500	0x550000
314	blk.34.ffn_down.weight	0x37df06500	0x8340000
315	blk.34.ffn_gate.weight	0x386246500	0x8340000
316	blk.34.ffn_norm.weight	0x38e586500	0x5000
317	blk.34.ffn_up.weight	0x38e58b500	0x8340000
318	blk.35.attn_k.weight	0x3968cb500	0x41a000
319	blk.35.attn_norm.weight	0x396ce5500	0x5000
320	blk.35.attn_output.weight	0x396cea500	0x1068000
321	blk.35.attn_q.weight	0x397d52500	0x1068000
322	blk.35.attn_v.weight	0x398dba500	0x550000
323	blk.35.ffn_down.weight	0x39930a500	0x8340000
324	blk.35.ffn_gate.weight	0x3a164a500	0x8340000
325	blk.35.ffn_norm.weight	0x3a998a500	0x5000
326	blk.35.ffn_up.weight	0x3a998f500	0x8340000
327	blk.36.attn_k.weight	0x3b1ccf500	0x41a000
328	blk.36.attn_norm.weight	0x3b20e9500	0x5000
329	blk.36.attn_output.weight	0x3b20ee500	0x1068000
330	blk.36.attn_q.weight	0x3b3156500	0x1068000
331	blk.36.attn_v.weight	0x3b41be500	0x550000
332	blk.36.ffn_down.weight	0x3b470e500	0x8340000
333	blk.36.ffn_gate.weight	0x3bca4e500	0x8340000
334	blk.36.ffn_norm.weight	0x3c4d8e500	0x5000
335	blk.36.ffn_up.weight	0x3c4d93500	0x8340000
336	blk.37.attn_k.weight	0x3cd0d3500	0x41a000
337	blk.37.attn_norm.weight	0x3cd4ed500	0x5000
338	blk.37.attn_output.weight	0x3cd4f2500	0x1068000
339	blk.37.attn_q.weight	0x3ce55a500	0x1068000
340	blk.37.attn_v.weight	0x3cf5c2500	0x550000
341	blk.37.ffn_down.weight	0x3cfb12500	0x8340000
342	blk.37.ffn_gate.weight	0x3d7e52500	0x8340000
343	blk.37.ffn_norm.weight	0x3e0192500	0x5000
344	blk.37.ffn_up.weight	0x3e0197500	0x8340000

Base Tensor Group : ~1B Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
0	output.weight	Output (W)	(~671M) 671088640	5120 x 131072 x 1 x 1	Q6_K
1	output_norm.weight	Output Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
2	token_embd.weight	Token Embedding (W)	(~671M) 671088640	5120 x 131072 x 1 x 1	Q3_K

• Total elements in base: ( ~1B) 1342182400
• Percentage of total elements: 5.98%

Block 0 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
3	blk.0.attn_k.weight	Block 0 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
4	blk.0.attn_norm.weight	Block 0 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
5	blk.0.attn_output.weight	Block 0 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
6	blk.0.attn_q.weight	Block 0 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
7	blk.0.attn_v.weight	Block 0 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
8	blk.0.ffn_down.weight	Block 0 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
9	blk.0.ffn_gate.weight	Block 0 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
10	blk.0.ffn_norm.weight	Block 0 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
11	blk.0.ffn_up.weight	Block 0 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.0: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 1 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
12	blk.1.attn_k.weight	Block 1 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
13	blk.1.attn_norm.weight	Block 1 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
14	blk.1.attn_output.weight	Block 1 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
15	blk.1.attn_q.weight	Block 1 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
16	blk.1.attn_v.weight	Block 1 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
17	blk.1.ffn_down.weight	Block 1 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
18	blk.1.ffn_gate.weight	Block 1 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
19	blk.1.ffn_norm.weight	Block 1 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
20	blk.1.ffn_up.weight	Block 1 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.1: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 2 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
21	blk.2.attn_k.weight	Block 2 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
22	blk.2.attn_norm.weight	Block 2 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
23	blk.2.attn_output.weight	Block 2 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
24	blk.2.attn_q.weight	Block 2 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
25	blk.2.attn_v.weight	Block 2 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
26	blk.2.ffn_down.weight	Block 2 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
27	blk.2.ffn_gate.weight	Block 2 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
28	blk.2.ffn_norm.weight	Block 2 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
29	blk.2.ffn_up.weight	Block 2 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.2: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 3 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
30	blk.3.attn_k.weight	Block 3 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
31	blk.3.attn_norm.weight	Block 3 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
32	blk.3.attn_output.weight	Block 3 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
33	blk.3.attn_q.weight	Block 3 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
34	blk.3.attn_v.weight	Block 3 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
35	blk.3.ffn_down.weight	Block 3 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
36	blk.3.ffn_gate.weight	Block 3 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
37	blk.3.ffn_norm.weight	Block 3 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
38	blk.3.ffn_up.weight	Block 3 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.3: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 4 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
39	blk.4.attn_k.weight	Block 4 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
40	blk.4.attn_norm.weight	Block 4 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
41	blk.4.attn_output.weight	Block 4 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
42	blk.4.attn_q.weight	Block 4 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
43	blk.4.attn_v.weight	Block 4 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
44	blk.4.ffn_down.weight	Block 4 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
45	blk.4.ffn_gate.weight	Block 4 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
46	blk.4.ffn_norm.weight	Block 4 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
47	blk.4.ffn_up.weight	Block 4 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.4: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 5 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
48	blk.5.attn_k.weight	Block 5 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
49	blk.5.attn_norm.weight	Block 5 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
50	blk.5.attn_output.weight	Block 5 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
51	blk.5.attn_q.weight	Block 5 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
52	blk.5.attn_v.weight	Block 5 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
53	blk.5.ffn_down.weight	Block 5 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
54	blk.5.ffn_gate.weight	Block 5 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
55	blk.5.ffn_norm.weight	Block 5 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
56	blk.5.ffn_up.weight	Block 5 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.5: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 6 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
57	blk.6.attn_k.weight	Block 6 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
58	blk.6.attn_norm.weight	Block 6 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
59	blk.6.attn_output.weight	Block 6 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
60	blk.6.attn_q.weight	Block 6 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
61	blk.6.attn_v.weight	Block 6 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
62	blk.6.ffn_down.weight	Block 6 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
63	blk.6.ffn_gate.weight	Block 6 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
64	blk.6.ffn_norm.weight	Block 6 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
65	blk.6.ffn_up.weight	Block 6 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.6: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 7 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
66	blk.7.attn_k.weight	Block 7 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
67	blk.7.attn_norm.weight	Block 7 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
68	blk.7.attn_output.weight	Block 7 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
69	blk.7.attn_q.weight	Block 7 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
70	blk.7.attn_v.weight	Block 7 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
71	blk.7.ffn_down.weight	Block 7 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
72	blk.7.ffn_gate.weight	Block 7 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
73	blk.7.ffn_norm.weight	Block 7 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
74	blk.7.ffn_up.weight	Block 7 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.7: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 8 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
75	blk.8.attn_k.weight	Block 8 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
76	blk.8.attn_norm.weight	Block 8 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
77	blk.8.attn_output.weight	Block 8 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
78	blk.8.attn_q.weight	Block 8 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
79	blk.8.attn_v.weight	Block 8 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
80	blk.8.ffn_down.weight	Block 8 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
81	blk.8.ffn_gate.weight	Block 8 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
82	blk.8.ffn_norm.weight	Block 8 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
83	blk.8.ffn_up.weight	Block 8 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.8: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 9 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
84	blk.9.attn_k.weight	Block 9 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
85	blk.9.attn_norm.weight	Block 9 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
86	blk.9.attn_output.weight	Block 9 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
87	blk.9.attn_q.weight	Block 9 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
88	blk.9.attn_v.weight	Block 9 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
89	blk.9.ffn_down.weight	Block 9 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
90	blk.9.ffn_gate.weight	Block 9 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
91	blk.9.ffn_norm.weight	Block 9 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
92	blk.9.ffn_up.weight	Block 9 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.9: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 10 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
93	blk.10.attn_k.weight	Block 10 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
94	blk.10.attn_norm.weight	Block 10 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
95	blk.10.attn_output.weight	Block 10 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
96	blk.10.attn_q.weight	Block 10 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
97	blk.10.attn_v.weight	Block 10 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
98	blk.10.ffn_down.weight	Block 10 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
99	blk.10.ffn_gate.weight	Block 10 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
100	blk.10.ffn_norm.weight	Block 10 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
101	blk.10.ffn_up.weight	Block 10 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.10: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 11 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
102	blk.11.attn_k.weight	Block 11 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
103	blk.11.attn_norm.weight	Block 11 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
104	blk.11.attn_output.weight	Block 11 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
105	blk.11.attn_q.weight	Block 11 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
106	blk.11.attn_v.weight	Block 11 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
107	blk.11.ffn_down.weight	Block 11 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
108	blk.11.ffn_gate.weight	Block 11 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
109	blk.11.ffn_norm.weight	Block 11 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
110	blk.11.ffn_up.weight	Block 11 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.11: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 12 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
111	blk.12.attn_k.weight	Block 12 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
112	blk.12.attn_norm.weight	Block 12 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
113	blk.12.attn_output.weight	Block 12 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
114	blk.12.attn_q.weight	Block 12 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
115	blk.12.attn_v.weight	Block 12 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
116	blk.12.ffn_down.weight	Block 12 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
117	blk.12.ffn_gate.weight	Block 12 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
118	blk.12.ffn_norm.weight	Block 12 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
119	blk.12.ffn_up.weight	Block 12 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.12: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 13 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
120	blk.13.attn_k.weight	Block 13 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
121	blk.13.attn_norm.weight	Block 13 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
122	blk.13.attn_output.weight	Block 13 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
123	blk.13.attn_q.weight	Block 13 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
124	blk.13.attn_v.weight	Block 13 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
125	blk.13.ffn_down.weight	Block 13 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
126	blk.13.ffn_gate.weight	Block 13 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
127	blk.13.ffn_norm.weight	Block 13 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
128	blk.13.ffn_up.weight	Block 13 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.13: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 14 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
129	blk.14.attn_k.weight	Block 14 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
130	blk.14.attn_norm.weight	Block 14 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
131	blk.14.attn_output.weight	Block 14 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
132	blk.14.attn_q.weight	Block 14 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
133	blk.14.attn_v.weight	Block 14 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
134	blk.14.ffn_down.weight	Block 14 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
135	blk.14.ffn_gate.weight	Block 14 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
136	blk.14.ffn_norm.weight	Block 14 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
137	blk.14.ffn_up.weight	Block 14 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.14: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 15 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
138	blk.15.attn_k.weight	Block 15 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
139	blk.15.attn_norm.weight	Block 15 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
140	blk.15.attn_output.weight	Block 15 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
141	blk.15.attn_q.weight	Block 15 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
142	blk.15.attn_v.weight	Block 15 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
143	blk.15.ffn_down.weight	Block 15 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
144	blk.15.ffn_gate.weight	Block 15 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
145	blk.15.ffn_norm.weight	Block 15 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
146	blk.15.ffn_up.weight	Block 15 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.15: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 16 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
147	blk.16.attn_k.weight	Block 16 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
148	blk.16.attn_norm.weight	Block 16 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
149	blk.16.attn_output.weight	Block 16 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
150	blk.16.attn_q.weight	Block 16 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
151	blk.16.attn_v.weight	Block 16 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
152	blk.16.ffn_down.weight	Block 16 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
153	blk.16.ffn_gate.weight	Block 16 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
154	blk.16.ffn_norm.weight	Block 16 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
155	blk.16.ffn_up.weight	Block 16 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.16: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 17 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
156	blk.17.attn_k.weight	Block 17 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
157	blk.17.attn_norm.weight	Block 17 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
158	blk.17.attn_output.weight	Block 17 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
159	blk.17.attn_q.weight	Block 17 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
160	blk.17.attn_v.weight	Block 17 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
161	blk.17.ffn_down.weight	Block 17 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
162	blk.17.ffn_gate.weight	Block 17 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
163	blk.17.ffn_norm.weight	Block 17 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
164	blk.17.ffn_up.weight	Block 17 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.17: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 18 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
165	blk.18.attn_k.weight	Block 18 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
166	blk.18.attn_norm.weight	Block 18 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
167	blk.18.attn_output.weight	Block 18 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
168	blk.18.attn_q.weight	Block 18 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
169	blk.18.attn_v.weight	Block 18 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
170	blk.18.ffn_down.weight	Block 18 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
171	blk.18.ffn_gate.weight	Block 18 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
172	blk.18.ffn_norm.weight	Block 18 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
173	blk.18.ffn_up.weight	Block 18 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.18: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 19 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
174	blk.19.attn_k.weight	Block 19 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
175	blk.19.attn_norm.weight	Block 19 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
176	blk.19.attn_output.weight	Block 19 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
177	blk.19.attn_q.weight	Block 19 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
178	blk.19.attn_v.weight	Block 19 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
179	blk.19.ffn_down.weight	Block 19 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
180	blk.19.ffn_gate.weight	Block 19 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
181	blk.19.ffn_norm.weight	Block 19 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
182	blk.19.ffn_up.weight	Block 19 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.19: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 20 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
183	blk.20.attn_k.weight	Block 20 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
184	blk.20.attn_norm.weight	Block 20 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
185	blk.20.attn_output.weight	Block 20 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
186	blk.20.attn_q.weight	Block 20 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
187	blk.20.attn_v.weight	Block 20 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
188	blk.20.ffn_down.weight	Block 20 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
189	blk.20.ffn_gate.weight	Block 20 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
190	blk.20.ffn_norm.weight	Block 20 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
191	blk.20.ffn_up.weight	Block 20 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.20: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 21 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
192	blk.21.attn_k.weight	Block 21 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
193	blk.21.attn_norm.weight	Block 21 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
194	blk.21.attn_output.weight	Block 21 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
195	blk.21.attn_q.weight	Block 21 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
196	blk.21.attn_v.weight	Block 21 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
197	blk.21.ffn_down.weight	Block 21 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
198	blk.21.ffn_gate.weight	Block 21 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
199	blk.21.ffn_norm.weight	Block 21 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
200	blk.21.ffn_up.weight	Block 21 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.21: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 22 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
201	blk.22.attn_k.weight	Block 22 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
202	blk.22.attn_norm.weight	Block 22 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
203	blk.22.attn_output.weight	Block 22 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
204	blk.22.attn_q.weight	Block 22 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
205	blk.22.attn_v.weight	Block 22 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
206	blk.22.ffn_down.weight	Block 22 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
207	blk.22.ffn_gate.weight	Block 22 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
208	blk.22.ffn_norm.weight	Block 22 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
209	blk.22.ffn_up.weight	Block 22 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.22: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 23 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
210	blk.23.attn_k.weight	Block 23 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
211	blk.23.attn_norm.weight	Block 23 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
212	blk.23.attn_output.weight	Block 23 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
213	blk.23.attn_q.weight	Block 23 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
214	blk.23.attn_v.weight	Block 23 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
215	blk.23.ffn_down.weight	Block 23 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
216	blk.23.ffn_gate.weight	Block 23 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
217	blk.23.ffn_norm.weight	Block 23 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
218	blk.23.ffn_up.weight	Block 23 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.23: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 24 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
219	blk.24.attn_k.weight	Block 24 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
220	blk.24.attn_norm.weight	Block 24 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
221	blk.24.attn_output.weight	Block 24 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
222	blk.24.attn_q.weight	Block 24 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
223	blk.24.attn_v.weight	Block 24 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
224	blk.24.ffn_down.weight	Block 24 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
225	blk.24.ffn_gate.weight	Block 24 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
226	blk.24.ffn_norm.weight	Block 24 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
227	blk.24.ffn_up.weight	Block 24 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.24: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 25 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
228	blk.25.attn_k.weight	Block 25 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q6_K
229	blk.25.attn_norm.weight	Block 25 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
230	blk.25.attn_output.weight	Block 25 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
231	blk.25.attn_q.weight	Block 25 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q6_K
232	blk.25.attn_v.weight	Block 25 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
233	blk.25.ffn_down.weight	Block 25 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
234	blk.25.ffn_gate.weight	Block 25 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
235	blk.25.ffn_norm.weight	Block 25 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
236	blk.25.ffn_up.weight	Block 25 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.25: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 26 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
237	blk.26.attn_k.weight	Block 26 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
238	blk.26.attn_norm.weight	Block 26 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
239	blk.26.attn_output.weight	Block 26 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
240	blk.26.attn_q.weight	Block 26 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
241	blk.26.attn_v.weight	Block 26 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
242	blk.26.ffn_down.weight	Block 26 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
243	blk.26.ffn_gate.weight	Block 26 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
244	blk.26.ffn_norm.weight	Block 26 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
245	blk.26.ffn_up.weight	Block 26 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.26: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 27 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
246	blk.27.attn_k.weight	Block 27 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
247	blk.27.attn_norm.weight	Block 27 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
248	blk.27.attn_output.weight	Block 27 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
249	blk.27.attn_q.weight	Block 27 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
250	blk.27.attn_v.weight	Block 27 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
251	blk.27.ffn_down.weight	Block 27 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
252	blk.27.ffn_gate.weight	Block 27 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
253	blk.27.ffn_norm.weight	Block 27 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
254	blk.27.ffn_up.weight	Block 27 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.27: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 28 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
255	blk.28.attn_k.weight	Block 28 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q6_K
256	blk.28.attn_norm.weight	Block 28 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
257	blk.28.attn_output.weight	Block 28 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
258	blk.28.attn_q.weight	Block 28 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q6_K
259	blk.28.attn_v.weight	Block 28 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
260	blk.28.ffn_down.weight	Block 28 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
261	blk.28.ffn_gate.weight	Block 28 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
262	blk.28.ffn_norm.weight	Block 28 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
263	blk.28.ffn_up.weight	Block 28 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.28: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 29 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
264	blk.29.attn_k.weight	Block 29 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
265	blk.29.attn_norm.weight	Block 29 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
266	blk.29.attn_output.weight	Block 29 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
267	blk.29.attn_q.weight	Block 29 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
268	blk.29.attn_v.weight	Block 29 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
269	blk.29.ffn_down.weight	Block 29 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
270	blk.29.ffn_gate.weight	Block 29 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K
271	blk.29.ffn_norm.weight	Block 29 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
272	blk.29.ffn_up.weight	Block 29 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q5_K

• Total elements in blk.29: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 30 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
273	blk.30.attn_k.weight	Block 30 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q6_K
274	blk.30.attn_norm.weight	Block 30 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
275	blk.30.attn_output.weight	Block 30 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
276	blk.30.attn_q.weight	Block 30 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q6_K
277	blk.30.attn_v.weight	Block 30 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
278	blk.30.ffn_down.weight	Block 30 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
279	blk.30.ffn_gate.weight	Block 30 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K
280	blk.30.ffn_norm.weight	Block 30 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
281	blk.30.ffn_up.weight	Block 30 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K

• Total elements in blk.30: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 31 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
282	blk.31.attn_k.weight	Block 31 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q5_K
283	blk.31.attn_norm.weight	Block 31 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
284	blk.31.attn_output.weight	Block 31 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
285	blk.31.attn_q.weight	Block 31 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q5_K
286	blk.31.attn_v.weight	Block 31 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
287	blk.31.ffn_down.weight	Block 31 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
288	blk.31.ffn_gate.weight	Block 31 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K
289	blk.31.ffn_norm.weight	Block 31 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
290	blk.31.ffn_up.weight	Block 31 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K

• Total elements in blk.31: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 32 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
291	blk.32.attn_k.weight	Block 32 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q6_K
292	blk.32.attn_norm.weight	Block 32 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
293	blk.32.attn_output.weight	Block 32 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
294	blk.32.attn_q.weight	Block 32 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q6_K
295	blk.32.attn_v.weight	Block 32 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
296	blk.32.ffn_down.weight	Block 32 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
297	blk.32.ffn_gate.weight	Block 32 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K
298	blk.32.ffn_norm.weight	Block 32 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
299	blk.32.ffn_up.weight	Block 32 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K

• Total elements in blk.32: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 33 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
300	blk.33.attn_k.weight	Block 33 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q6_K
301	blk.33.attn_norm.weight	Block 33 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
302	blk.33.attn_output.weight	Block 33 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
303	blk.33.attn_q.weight	Block 33 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q6_K
304	blk.33.attn_v.weight	Block 33 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
305	blk.33.ffn_down.weight	Block 33 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
306	blk.33.ffn_gate.weight	Block 33 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K
307	blk.33.ffn_norm.weight	Block 33 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
308	blk.33.ffn_up.weight	Block 33 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K

• Total elements in blk.33: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 34 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
309	blk.34.attn_k.weight	Block 34 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q6_K
310	blk.34.attn_norm.weight	Block 34 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
311	blk.34.attn_output.weight	Block 34 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
312	blk.34.attn_q.weight	Block 34 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q6_K
313	blk.34.attn_v.weight	Block 34 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
314	blk.34.ffn_down.weight	Block 34 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
315	blk.34.ffn_gate.weight	Block 34 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K
316	blk.34.ffn_norm.weight	Block 34 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
317	blk.34.ffn_up.weight	Block 34 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K

• Total elements in blk.34: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 35 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
318	blk.35.attn_k.weight	Block 35 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q6_K
319	blk.35.attn_norm.weight	Block 35 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
320	blk.35.attn_output.weight	Block 35 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
321	blk.35.attn_q.weight	Block 35 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q6_K
322	blk.35.attn_v.weight	Block 35 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
323	blk.35.ffn_down.weight	Block 35 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
324	blk.35.ffn_gate.weight	Block 35 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K
325	blk.35.ffn_norm.weight	Block 35 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
326	blk.35.ffn_up.weight	Block 35 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K

• Total elements in blk.35: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 36 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
327	blk.36.attn_k.weight	Block 36 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q6_K
328	blk.36.attn_norm.weight	Block 36 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
329	blk.36.attn_output.weight	Block 36 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
330	blk.36.attn_q.weight	Block 36 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q6_K
331	blk.36.attn_v.weight	Block 36 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
332	blk.36.ffn_down.weight	Block 36 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
333	blk.36.ffn_gate.weight	Block 36 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K
334	blk.36.ffn_norm.weight	Block 36 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
335	blk.36.ffn_up.weight	Block 36 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K

• Total elements in blk.36: (~556M) 555755520
• Percentage of total elements: 2.47%

Block 37 Tensor Group : ~556M Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
336	blk.37.attn_k.weight	Block 37 Attention Key (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q6_K
337	blk.37.attn_norm.weight	Block 37 Attention Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
338	blk.37.attn_output.weight	Block 37 Attention Output (W)	( ~21M) 20971520	4096 x 5120 x 1 x 1	Q6_K
339	blk.37.attn_q.weight	Block 37 Attention Query (W)	( ~21M) 20971520	5120 x 4096 x 1 x 1	Q6_K
340	blk.37.attn_v.weight	Block 37 Attention Value (W)	( ~5M) 5242880	5120 x 1024 x 1 x 1	Q8_0
341	blk.37.ffn_down.weight	Block 37 Feed-Forward Network "Down" (W)	(~168M) 167772160	32768 x 5120 x 1 x 1	Q6_K
342	blk.37.ffn_gate.weight	Block 37 Feed-Forward Network "Gate" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K
343	blk.37.ffn_norm.weight	Block 37 Feed-Forward Network Normalization (W)	( ~5K) 5120	5120 x 1 x 1 x 1	F32
344	blk.37.ffn_up.weight	Block 37 Feed-Forward Network "Up" (W)	(~168M) 167772160	5120 x 32768 x 1 x 1	Q6_K

• Total elements in blk.37: (~556M) 555755520
• Percentage of total elements: 2.47%