scores/DeepSeek-R1-Distill-Llama-8B-F16.md

DeepSeek-R1-Distill-Llama-8B-F16.gguf - GGUF Internal File Dump

• Endian: LITTLE endian

Key Value Metadata Store

There are 32 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	29
4	STRING	1	general.architecture	llama
5	STRING	1	general.type	model
6	STRING	1	general.name	DeepSeek R1 Distill Llama 8B
7	STRING	1	general.basename	DeepSeek-R1-Distill-Llama
8	STRING	1	general.size_label	8B
9	STRING	1	general.license	mit
10	UINT32	1	llama.block_count	32
11	UINT32	1	llama.context_length	131072
12	UINT32	1	llama.embedding_length	4096
13	UINT32	1	llama.feed_forward_length	14336
14	UINT32	1	llama.attention.head_count	32
15	UINT32	1	llama.attention.head_count_kv	8
16	FLOAT32	1	llama.rope.freq_base	500000.0
17	FLOAT32	1	llama.attention.layer_norm_rms_epsilon	1e-05
18	UINT32	1	general.file_type	1
19	UINT32	1	llama.vocab_size	128256
20	UINT32	1	llama.rope.dimension_count	128
21	STRING	1	tokenizer.ggml.model	gpt2
22	STRING	1	tokenizer.ggml.pre	llama-bpe
23	[STRING]	128256	tokenizer.ggml.tokens	[ !, ", #, $, %, ... ]
24	[INT32]	128256	tokenizer.ggml.token_type	[ 1, 1, 1, 1, 1, 1, 1, ... ]
25	[STRING]	280147	tokenizer.ggml.merges	[ Ġ Ġ, Ġ ĠĠĠ, ĠĠ ĠĠ, ĠĠĠ Ġ, i n, ... ]
26	UINT32	1	tokenizer.ggml.bos_token_id	128000
27	UINT32	1	tokenizer.ggml.eos_token_id	128001
28	UINT32	1	tokenizer.ggml.padding_token_id	128001
29	BOOL	1	tokenizer.ggml.add_bos_token	True
30	BOOL	1	tokenizer.ggml.add_eos_token	False
31	STRING	1	tokenizer.chat_template	{% if not add_generation_promp...{{'<｜Assistant｜>'}}{% endif %}
32	UINT32	1	general.quantization_version	2

Tensors Overview ~8B Elements

Total number of elements in all tensors: 8030261312 Elements

• DeepSeek-R1-Distill-Llama-8B-F16.gguf - GGUF Internal File Dump
  • Key Value Metadata Store
  • Tensors Overview ~8B Elements
    • Tensor Data Offset
    • Base Tensor Group : ~1B Elements
    • Block 0 Tensor Group : ~218M Elements
    • Block 1 Tensor Group : ~218M Elements
    • Block 10 Tensor Group : ~218M Elements
    • Block 11 Tensor Group : ~218M Elements
    • Block 12 Tensor Group : ~218M Elements
    • Block 13 Tensor Group : ~218M Elements
    • Block 14 Tensor Group : ~218M Elements
    • Block 15 Tensor Group : ~218M Elements
    • Block 16 Tensor Group : ~218M Elements
    • Block 17 Tensor Group : ~218M Elements
    • Block 2 Tensor Group : ~218M Elements
    • Block 3 Tensor Group : ~218M Elements
    • Block 4 Tensor Group : ~218M Elements
    • Block 5 Tensor Group : ~218M Elements
    • Block 6 Tensor Group : ~218M Elements
    • Block 7 Tensor Group : ~218M Elements
    • Block 8 Tensor Group : ~218M Elements
    • Block 9 Tensor Group : ~218M Elements
    • Block 18 Tensor Group : ~218M Elements
    • Block 19 Tensor Group : ~218M Elements
    • Block 20 Tensor Group : ~218M Elements
    • Block 21 Tensor Group : ~218M Elements
    • Block 22 Tensor Group : ~218M Elements
    • Block 23 Tensor Group : ~218M Elements
    • Block 24 Tensor Group : ~218M Elements
    • Block 25 Tensor Group : ~218M Elements
    • Block 26 Tensor Group : ~218M Elements
    • Block 27 Tensor Group : ~218M Elements
    • Block 28 Tensor Group : ~218M Elements
    • Block 29 Tensor Group : ~218M Elements
    • Block 30 Tensor Group : ~218M Elements
    • Block 31 Tensor Group : ~218M 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	rope_freqs.weight	0x779960	0x100
1	token_embd.weight	0x779a60	0x3ea00000
2	blk.0.attn_norm.weight	0x3f179a60	0x4000
3	blk.0.ffn_down.weight	0x3f17da60	0x7000000
4	blk.0.ffn_gate.weight	0x4617da60	0x7000000
5	blk.0.ffn_up.weight	0x4d17da60	0x7000000
6	blk.0.ffn_norm.weight	0x5417da60	0x4000
7	blk.0.attn_k.weight	0x54181a60	0x800000
8	blk.0.attn_output.weight	0x54981a60	0x2000000
9	blk.0.attn_q.weight	0x56981a60	0x2000000
10	blk.0.attn_v.weight	0x58981a60	0x800000
11	blk.1.attn_norm.weight	0x59181a60	0x4000
12	blk.1.ffn_down.weight	0x59185a60	0x7000000
13	blk.1.ffn_gate.weight	0x60185a60	0x7000000
14	blk.1.ffn_up.weight	0x67185a60	0x7000000
15	blk.1.ffn_norm.weight	0x6e185a60	0x4000
16	blk.1.attn_k.weight	0x6e189a60	0x800000
17	blk.1.attn_output.weight	0x6e989a60	0x2000000
18	blk.1.attn_q.weight	0x70989a60	0x2000000
19	blk.1.attn_v.weight	0x72989a60	0x800000
20	blk.10.attn_norm.weight	0x73189a60	0x4000
21	blk.10.ffn_down.weight	0x7318da60	0x7000000
22	blk.10.ffn_gate.weight	0x7a18da60	0x7000000
23	blk.10.ffn_up.weight	0x8118da60	0x7000000
24	blk.10.ffn_norm.weight	0x8818da60	0x4000
25	blk.10.attn_k.weight	0x88191a60	0x800000
26	blk.10.attn_output.weight	0x88991a60	0x2000000
27	blk.10.attn_q.weight	0x8a991a60	0x2000000
28	blk.10.attn_v.weight	0x8c991a60	0x800000
29	blk.11.attn_norm.weight	0x8d191a60	0x4000
30	blk.11.ffn_down.weight	0x8d195a60	0x7000000
31	blk.11.ffn_gate.weight	0x94195a60	0x7000000
32	blk.11.ffn_up.weight	0x9b195a60	0x7000000
33	blk.11.ffn_norm.weight	0xa2195a60	0x4000
34	blk.11.attn_k.weight	0xa2199a60	0x800000
35	blk.11.attn_output.weight	0xa2999a60	0x2000000
36	blk.11.attn_q.weight	0xa4999a60	0x2000000
37	blk.11.attn_v.weight	0xa6999a60	0x800000
38	blk.12.attn_norm.weight	0xa7199a60	0x4000
39	blk.12.ffn_down.weight	0xa719da60	0x7000000
40	blk.12.ffn_gate.weight	0xae19da60	0x7000000
41	blk.12.ffn_up.weight	0xb519da60	0x7000000
42	blk.12.ffn_norm.weight	0xbc19da60	0x4000
43	blk.12.attn_k.weight	0xbc1a1a60	0x800000
44	blk.12.attn_output.weight	0xbc9a1a60	0x2000000
45	blk.12.attn_q.weight	0xbe9a1a60	0x2000000
46	blk.12.attn_v.weight	0xc09a1a60	0x800000
47	blk.13.attn_norm.weight	0xc11a1a60	0x4000
48	blk.13.ffn_down.weight	0xc11a5a60	0x7000000
49	blk.13.ffn_gate.weight	0xc81a5a60	0x7000000
50	blk.13.ffn_up.weight	0xcf1a5a60	0x7000000
51	blk.13.ffn_norm.weight	0xd61a5a60	0x4000
52	blk.13.attn_k.weight	0xd61a9a60	0x800000
53	blk.13.attn_output.weight	0xd69a9a60	0x2000000
54	blk.13.attn_q.weight	0xd89a9a60	0x2000000
55	blk.13.attn_v.weight	0xda9a9a60	0x800000
56	blk.14.attn_norm.weight	0xdb1a9a60	0x4000
57	blk.14.ffn_down.weight	0xdb1ada60	0x7000000
58	blk.14.ffn_gate.weight	0xe21ada60	0x7000000
59	blk.14.ffn_up.weight	0xe91ada60	0x7000000
60	blk.14.ffn_norm.weight	0xf01ada60	0x4000
61	blk.14.attn_k.weight	0xf01b1a60	0x800000
62	blk.14.attn_output.weight	0xf09b1a60	0x2000000
63	blk.14.attn_q.weight	0xf29b1a60	0x2000000
64	blk.14.attn_v.weight	0xf49b1a60	0x800000
65	blk.15.attn_norm.weight	0xf51b1a60	0x4000
66	blk.15.ffn_down.weight	0xf51b5a60	0x7000000
67	blk.15.ffn_gate.weight	0xfc1b5a60	0x7000000
68	blk.15.ffn_up.weight	0x1031b5a60	0x7000000
69	blk.15.ffn_norm.weight	0x10a1b5a60	0x4000
70	blk.15.attn_k.weight	0x10a1b9a60	0x800000
71	blk.15.attn_output.weight	0x10a9b9a60	0x2000000
72	blk.15.attn_q.weight	0x10c9b9a60	0x2000000
73	blk.15.attn_v.weight	0x10e9b9a60	0x800000
74	blk.16.attn_norm.weight	0x10f1b9a60	0x4000
75	blk.16.ffn_down.weight	0x10f1bda60	0x7000000
76	blk.16.ffn_gate.weight	0x1161bda60	0x7000000
77	blk.16.ffn_up.weight	0x11d1bda60	0x7000000
78	blk.16.ffn_norm.weight	0x1241bda60	0x4000
79	blk.16.attn_k.weight	0x1241c1a60	0x800000
80	blk.16.attn_output.weight	0x1249c1a60	0x2000000
81	blk.16.attn_q.weight	0x1269c1a60	0x2000000
82	blk.16.attn_v.weight	0x1289c1a60	0x800000
83	blk.17.ffn_gate.weight	0x1291c1a60	0x7000000
84	blk.17.attn_k.weight	0x1301c1a60	0x800000
85	blk.17.attn_output.weight	0x1309c1a60	0x2000000
86	blk.17.attn_q.weight	0x1329c1a60	0x2000000
87	blk.17.attn_v.weight	0x1349c1a60	0x800000
88	blk.2.attn_norm.weight	0x1351c1a60	0x4000
89	blk.2.ffn_down.weight	0x1351c5a60	0x7000000
90	blk.2.ffn_gate.weight	0x13c1c5a60	0x7000000
91	blk.2.ffn_up.weight	0x1431c5a60	0x7000000
92	blk.2.ffn_norm.weight	0x14a1c5a60	0x4000
93	blk.2.attn_k.weight	0x14a1c9a60	0x800000
94	blk.2.attn_output.weight	0x14a9c9a60	0x2000000
95	blk.2.attn_q.weight	0x14c9c9a60	0x2000000
96	blk.2.attn_v.weight	0x14e9c9a60	0x800000
97	blk.3.attn_norm.weight	0x14f1c9a60	0x4000
98	blk.3.ffn_down.weight	0x14f1cda60	0x7000000
99	blk.3.ffn_gate.weight	0x1561cda60	0x7000000
100	blk.3.ffn_up.weight	0x15d1cda60	0x7000000
101	blk.3.ffn_norm.weight	0x1641cda60	0x4000
102	blk.3.attn_k.weight	0x1641d1a60	0x800000
103	blk.3.attn_output.weight	0x1649d1a60	0x2000000
104	blk.3.attn_q.weight	0x1669d1a60	0x2000000
105	blk.3.attn_v.weight	0x1689d1a60	0x800000
106	blk.4.attn_norm.weight	0x1691d1a60	0x4000
107	blk.4.ffn_down.weight	0x1691d5a60	0x7000000
108	blk.4.ffn_gate.weight	0x1701d5a60	0x7000000
109	blk.4.ffn_up.weight	0x1771d5a60	0x7000000
110	blk.4.ffn_norm.weight	0x17e1d5a60	0x4000
111	blk.4.attn_k.weight	0x17e1d9a60	0x800000
112	blk.4.attn_output.weight	0x17e9d9a60	0x2000000
113	blk.4.attn_q.weight	0x1809d9a60	0x2000000
114	blk.4.attn_v.weight	0x1829d9a60	0x800000
115	blk.5.attn_norm.weight	0x1831d9a60	0x4000
116	blk.5.ffn_down.weight	0x1831dda60	0x7000000
117	blk.5.ffn_gate.weight	0x18a1dda60	0x7000000
118	blk.5.ffn_up.weight	0x1911dda60	0x7000000
119	blk.5.ffn_norm.weight	0x1981dda60	0x4000
120	blk.5.attn_k.weight	0x1981e1a60	0x800000
121	blk.5.attn_output.weight	0x1989e1a60	0x2000000
122	blk.5.attn_q.weight	0x19a9e1a60	0x2000000
123	blk.5.attn_v.weight	0x19c9e1a60	0x800000
124	blk.6.attn_norm.weight	0x19d1e1a60	0x4000
125	blk.6.ffn_down.weight	0x19d1e5a60	0x7000000
126	blk.6.ffn_gate.weight	0x1a41e5a60	0x7000000
127	blk.6.ffn_up.weight	0x1ab1e5a60	0x7000000
128	blk.6.ffn_norm.weight	0x1b21e5a60	0x4000
129	blk.6.attn_k.weight	0x1b21e9a60	0x800000
130	blk.6.attn_output.weight	0x1b29e9a60	0x2000000
131	blk.6.attn_q.weight	0x1b49e9a60	0x2000000
132	blk.6.attn_v.weight	0x1b69e9a60	0x800000
133	blk.7.attn_norm.weight	0x1b71e9a60	0x4000
134	blk.7.ffn_down.weight	0x1b71eda60	0x7000000
135	blk.7.ffn_gate.weight	0x1be1eda60	0x7000000
136	blk.7.ffn_up.weight	0x1c51eda60	0x7000000
137	blk.7.ffn_norm.weight	0x1cc1eda60	0x4000
138	blk.7.attn_k.weight	0x1cc1f1a60	0x800000
139	blk.7.attn_output.weight	0x1cc9f1a60	0x2000000
140	blk.7.attn_q.weight	0x1ce9f1a60	0x2000000
141	blk.7.attn_v.weight	0x1d09f1a60	0x800000
142	blk.8.attn_norm.weight	0x1d11f1a60	0x4000
143	blk.8.ffn_down.weight	0x1d11f5a60	0x7000000
144	blk.8.ffn_gate.weight	0x1d81f5a60	0x7000000
145	blk.8.ffn_up.weight	0x1df1f5a60	0x7000000
146	blk.8.ffn_norm.weight	0x1e61f5a60	0x4000
147	blk.8.attn_k.weight	0x1e61f9a60	0x800000
148	blk.8.attn_output.weight	0x1e69f9a60	0x2000000
149	blk.8.attn_q.weight	0x1e89f9a60	0x2000000
150	blk.8.attn_v.weight	0x1ea9f9a60	0x800000
151	blk.9.attn_norm.weight	0x1eb1f9a60	0x4000
152	blk.9.ffn_down.weight	0x1eb1fda60	0x7000000
153	blk.9.ffn_gate.weight	0x1f21fda60	0x7000000
154	blk.9.ffn_up.weight	0x1f91fda60	0x7000000
155	blk.9.ffn_norm.weight	0x2001fda60	0x4000
156	blk.9.attn_k.weight	0x200201a60	0x800000
157	blk.9.attn_output.weight	0x200a01a60	0x2000000
158	blk.9.attn_q.weight	0x202a01a60	0x2000000
159	blk.9.attn_v.weight	0x204a01a60	0x800000
160	output.weight	0x205201a60	0x3ea00000
161	blk.17.attn_norm.weight	0x243c01a60	0x4000
162	blk.17.ffn_down.weight	0x243c05a60	0x7000000
163	blk.17.ffn_up.weight	0x24ac05a60	0x7000000
164	blk.17.ffn_norm.weight	0x251c05a60	0x4000
165	blk.18.attn_norm.weight	0x251c09a60	0x4000
166	blk.18.ffn_down.weight	0x251c0da60	0x7000000
167	blk.18.ffn_gate.weight	0x258c0da60	0x7000000
168	blk.18.ffn_up.weight	0x25fc0da60	0x7000000
169	blk.18.ffn_norm.weight	0x266c0da60	0x4000
170	blk.18.attn_k.weight	0x266c11a60	0x800000
171	blk.18.attn_output.weight	0x267411a60	0x2000000
172	blk.18.attn_q.weight	0x269411a60	0x2000000
173	blk.18.attn_v.weight	0x26b411a60	0x800000
174	blk.19.attn_norm.weight	0x26bc11a60	0x4000
175	blk.19.ffn_down.weight	0x26bc15a60	0x7000000
176	blk.19.ffn_gate.weight	0x272c15a60	0x7000000
177	blk.19.ffn_up.weight	0x279c15a60	0x7000000
178	blk.19.ffn_norm.weight	0x280c15a60	0x4000
179	blk.19.attn_k.weight	0x280c19a60	0x800000
180	blk.19.attn_output.weight	0x281419a60	0x2000000
181	blk.19.attn_q.weight	0x283419a60	0x2000000
182	blk.19.attn_v.weight	0x285419a60	0x800000
183	blk.20.attn_norm.weight	0x285c19a60	0x4000
184	blk.20.ffn_down.weight	0x285c1da60	0x7000000
185	blk.20.ffn_gate.weight	0x28cc1da60	0x7000000
186	blk.20.ffn_up.weight	0x293c1da60	0x7000000
187	blk.20.ffn_norm.weight	0x29ac1da60	0x4000
188	blk.20.attn_k.weight	0x29ac21a60	0x800000
189	blk.20.attn_output.weight	0x29b421a60	0x2000000
190	blk.20.attn_q.weight	0x29d421a60	0x2000000
191	blk.20.attn_v.weight	0x29f421a60	0x800000
192	blk.21.attn_norm.weight	0x29fc21a60	0x4000
193	blk.21.ffn_down.weight	0x29fc25a60	0x7000000
194	blk.21.ffn_gate.weight	0x2a6c25a60	0x7000000
195	blk.21.ffn_up.weight	0x2adc25a60	0x7000000
196	blk.21.ffn_norm.weight	0x2b4c25a60	0x4000
197	blk.21.attn_k.weight	0x2b4c29a60	0x800000
198	blk.21.attn_output.weight	0x2b5429a60	0x2000000
199	blk.21.attn_q.weight	0x2b7429a60	0x2000000
200	blk.21.attn_v.weight	0x2b9429a60	0x800000
201	blk.22.attn_norm.weight	0x2b9c29a60	0x4000
202	blk.22.ffn_down.weight	0x2b9c2da60	0x7000000
203	blk.22.ffn_gate.weight	0x2c0c2da60	0x7000000
204	blk.22.ffn_up.weight	0x2c7c2da60	0x7000000
205	blk.22.ffn_norm.weight	0x2cec2da60	0x4000
206	blk.22.attn_k.weight	0x2cec31a60	0x800000
207	blk.22.attn_output.weight	0x2cf431a60	0x2000000
208	blk.22.attn_q.weight	0x2d1431a60	0x2000000
209	blk.22.attn_v.weight	0x2d3431a60	0x800000
210	blk.23.attn_norm.weight	0x2d3c31a60	0x4000
211	blk.23.ffn_down.weight	0x2d3c35a60	0x7000000
212	blk.23.ffn_gate.weight	0x2dac35a60	0x7000000
213	blk.23.ffn_up.weight	0x2e1c35a60	0x7000000
214	blk.23.ffn_norm.weight	0x2e8c35a60	0x4000
215	blk.23.attn_k.weight	0x2e8c39a60	0x800000
216	blk.23.attn_output.weight	0x2e9439a60	0x2000000
217	blk.23.attn_q.weight	0x2eb439a60	0x2000000
218	blk.23.attn_v.weight	0x2ed439a60	0x800000
219	blk.24.attn_norm.weight	0x2edc39a60	0x4000
220	blk.24.ffn_down.weight	0x2edc3da60	0x7000000
221	blk.24.ffn_gate.weight	0x2f4c3da60	0x7000000
222	blk.24.ffn_up.weight	0x2fbc3da60	0x7000000
223	blk.24.ffn_norm.weight	0x302c3da60	0x4000
224	blk.24.attn_k.weight	0x302c41a60	0x800000
225	blk.24.attn_output.weight	0x303441a60	0x2000000
226	blk.24.attn_q.weight	0x305441a60	0x2000000
227	blk.24.attn_v.weight	0x307441a60	0x800000
228	blk.25.attn_norm.weight	0x307c41a60	0x4000
229	blk.25.ffn_down.weight	0x307c45a60	0x7000000
230	blk.25.ffn_gate.weight	0x30ec45a60	0x7000000
231	blk.25.ffn_up.weight	0x315c45a60	0x7000000
232	blk.25.ffn_norm.weight	0x31cc45a60	0x4000
233	blk.25.attn_k.weight	0x31cc49a60	0x800000
234	blk.25.attn_output.weight	0x31d449a60	0x2000000
235	blk.25.attn_q.weight	0x31f449a60	0x2000000
236	blk.25.attn_v.weight	0x321449a60	0x800000
237	blk.26.attn_norm.weight	0x321c49a60	0x4000
238	blk.26.ffn_down.weight	0x321c4da60	0x7000000
239	blk.26.ffn_gate.weight	0x328c4da60	0x7000000
240	blk.26.ffn_up.weight	0x32fc4da60	0x7000000
241	blk.26.ffn_norm.weight	0x336c4da60	0x4000
242	blk.26.attn_k.weight	0x336c51a60	0x800000
243	blk.26.attn_output.weight	0x337451a60	0x2000000
244	blk.26.attn_q.weight	0x339451a60	0x2000000
245	blk.26.attn_v.weight	0x33b451a60	0x800000
246	blk.27.attn_norm.weight	0x33bc51a60	0x4000
247	blk.27.ffn_down.weight	0x33bc55a60	0x7000000
248	blk.27.ffn_gate.weight	0x342c55a60	0x7000000
249	blk.27.ffn_up.weight	0x349c55a60	0x7000000
250	blk.27.ffn_norm.weight	0x350c55a60	0x4000
251	blk.27.attn_k.weight	0x350c59a60	0x800000
252	blk.27.attn_output.weight	0x351459a60	0x2000000
253	blk.27.attn_q.weight	0x353459a60	0x2000000
254	blk.27.attn_v.weight	0x355459a60	0x800000
255	blk.28.attn_norm.weight	0x355c59a60	0x4000
256	blk.28.ffn_down.weight	0x355c5da60	0x7000000
257	blk.28.ffn_gate.weight	0x35cc5da60	0x7000000
258	blk.28.ffn_up.weight	0x363c5da60	0x7000000
259	blk.28.ffn_norm.weight	0x36ac5da60	0x4000
260	blk.28.attn_k.weight	0x36ac61a60	0x800000
261	blk.28.attn_output.weight	0x36b461a60	0x2000000
262	blk.28.attn_q.weight	0x36d461a60	0x2000000
263	blk.28.attn_v.weight	0x36f461a60	0x800000
264	blk.29.attn_norm.weight	0x36fc61a60	0x4000
265	blk.29.ffn_down.weight	0x36fc65a60	0x7000000
266	blk.29.ffn_gate.weight	0x376c65a60	0x7000000
267	blk.29.ffn_up.weight	0x37dc65a60	0x7000000
268	blk.29.ffn_norm.weight	0x384c65a60	0x4000
269	blk.29.attn_k.weight	0x384c69a60	0x800000
270	blk.29.attn_output.weight	0x385469a60	0x2000000
271	blk.29.attn_q.weight	0x387469a60	0x2000000
272	blk.29.attn_v.weight	0x389469a60	0x800000
273	blk.30.attn_norm.weight	0x389c69a60	0x4000
274	blk.30.ffn_down.weight	0x389c6da60	0x7000000
275	blk.30.ffn_gate.weight	0x390c6da60	0x7000000
276	blk.30.ffn_up.weight	0x397c6da60	0x7000000
277	blk.30.ffn_norm.weight	0x39ec6da60	0x4000
278	blk.30.attn_k.weight	0x39ec71a60	0x800000
279	blk.30.attn_output.weight	0x39f471a60	0x2000000
280	blk.30.attn_q.weight	0x3a1471a60	0x2000000
281	blk.30.attn_v.weight	0x3a3471a60	0x800000
282	blk.31.attn_norm.weight	0x3a3c71a60	0x4000
283	blk.31.ffn_down.weight	0x3a3c75a60	0x7000000
284	blk.31.ffn_gate.weight	0x3aac75a60	0x7000000
285	blk.31.ffn_up.weight	0x3b1c75a60	0x7000000
286	blk.31.ffn_norm.weight	0x3b8c75a60	0x4000
287	blk.31.attn_k.weight	0x3b8c79a60	0x800000
288	blk.31.attn_output.weight	0x3b9479a60	0x2000000
289	blk.31.attn_q.weight	0x3bb479a60	0x2000000
290	blk.31.attn_v.weight	0x3bd479a60	0x800000
291	output_norm.weight	0x3bdc79a60	0x4000

Base Tensor Group : ~1B Elements

T_ID	Tensor Layer Name	Human Friendly Tensor Layer Name	Elements	Shape	Type
0	rope_freqs.weight	Rope_Freqs (W)	( 64) 64	64 x 1 x 1 x 1	F32
1	token_embd.weight	Token Embedding (W)	(~525M) 525336576	4096 x 128256 x 1 x 1	F16
160	output.weight	Output (W)	(~525M) 525336576	4096 x 128256 x 1 x 1	F16
291	output_norm.weight	Output Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32

• 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
2	blk.0.attn_norm.weight	Block 0 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
3	blk.0.ffn_down.weight	Block 0 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
4	blk.0.ffn_gate.weight	Block 0 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
5	blk.0.ffn_up.weight	Block 0 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
6	blk.0.ffn_norm.weight	Block 0 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
7	blk.0.attn_k.weight	Block 0 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
8	blk.0.attn_output.weight	Block 0 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
9	blk.0.attn_q.weight	Block 0 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
10	blk.0.attn_v.weight	Block 0 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
11	blk.1.attn_norm.weight	Block 1 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
12	blk.1.ffn_down.weight	Block 1 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
13	blk.1.ffn_gate.weight	Block 1 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
14	blk.1.ffn_up.weight	Block 1 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
15	blk.1.ffn_norm.weight	Block 1 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
16	blk.1.attn_k.weight	Block 1 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
17	blk.1.attn_output.weight	Block 1 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
18	blk.1.attn_q.weight	Block 1 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
19	blk.1.attn_v.weight	Block 1 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• Total elements in blk.1: (~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
20	blk.10.attn_norm.weight	Block 10 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
21	blk.10.ffn_down.weight	Block 10 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
22	blk.10.ffn_gate.weight	Block 10 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
23	blk.10.ffn_up.weight	Block 10 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
24	blk.10.ffn_norm.weight	Block 10 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
25	blk.10.attn_k.weight	Block 10 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
26	blk.10.attn_output.weight	Block 10 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
27	blk.10.attn_q.weight	Block 10 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
28	blk.10.attn_v.weight	Block 10 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
29	blk.11.attn_norm.weight	Block 11 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
30	blk.11.ffn_down.weight	Block 11 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
31	blk.11.ffn_gate.weight	Block 11 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
32	blk.11.ffn_up.weight	Block 11 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
33	blk.11.ffn_norm.weight	Block 11 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
34	blk.11.attn_k.weight	Block 11 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
35	blk.11.attn_output.weight	Block 11 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
36	blk.11.attn_q.weight	Block 11 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
37	blk.11.attn_v.weight	Block 11 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
38	blk.12.attn_norm.weight	Block 12 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
39	blk.12.ffn_down.weight	Block 12 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
40	blk.12.ffn_gate.weight	Block 12 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
41	blk.12.ffn_up.weight	Block 12 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
42	blk.12.ffn_norm.weight	Block 12 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
43	blk.12.attn_k.weight	Block 12 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
44	blk.12.attn_output.weight	Block 12 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
45	blk.12.attn_q.weight	Block 12 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
46	blk.12.attn_v.weight	Block 12 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
47	blk.13.attn_norm.weight	Block 13 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
48	blk.13.ffn_down.weight	Block 13 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
49	blk.13.ffn_gate.weight	Block 13 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
50	blk.13.ffn_up.weight	Block 13 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
51	blk.13.ffn_norm.weight	Block 13 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
52	blk.13.attn_k.weight	Block 13 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
53	blk.13.attn_output.weight	Block 13 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
54	blk.13.attn_q.weight	Block 13 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
55	blk.13.attn_v.weight	Block 13 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
56	blk.14.attn_norm.weight	Block 14 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
57	blk.14.ffn_down.weight	Block 14 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
58	blk.14.ffn_gate.weight	Block 14 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
59	blk.14.ffn_up.weight	Block 14 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
60	blk.14.ffn_norm.weight	Block 14 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
61	blk.14.attn_k.weight	Block 14 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
62	blk.14.attn_output.weight	Block 14 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
63	blk.14.attn_q.weight	Block 14 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
64	blk.14.attn_v.weight	Block 14 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
65	blk.15.attn_norm.weight	Block 15 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
66	blk.15.ffn_down.weight	Block 15 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
67	blk.15.ffn_gate.weight	Block 15 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
68	blk.15.ffn_up.weight	Block 15 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
69	blk.15.ffn_norm.weight	Block 15 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
70	blk.15.attn_k.weight	Block 15 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
71	blk.15.attn_output.weight	Block 15 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
72	blk.15.attn_q.weight	Block 15 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
73	blk.15.attn_v.weight	Block 15 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
74	blk.16.attn_norm.weight	Block 16 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
75	blk.16.ffn_down.weight	Block 16 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
76	blk.16.ffn_gate.weight	Block 16 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
77	blk.16.ffn_up.weight	Block 16 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
78	blk.16.ffn_norm.weight	Block 16 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
79	blk.16.attn_k.weight	Block 16 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
80	blk.16.attn_output.weight	Block 16 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
81	blk.16.attn_q.weight	Block 16 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
82	blk.16.attn_v.weight	Block 16 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
83	blk.17.ffn_gate.weight	Block 17 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
84	blk.17.attn_k.weight	Block 17 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
85	blk.17.attn_output.weight	Block 17 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
86	blk.17.attn_q.weight	Block 17 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
87	blk.17.attn_v.weight	Block 17 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
161	blk.17.attn_norm.weight	Block 17 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
162	blk.17.ffn_down.weight	Block 17 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
163	blk.17.ffn_up.weight	Block 17 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
164	blk.17.ffn_norm.weight	Block 17 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32

• Total elements in blk.17: (~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
88	blk.2.attn_norm.weight	Block 2 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
89	blk.2.ffn_down.weight	Block 2 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
90	blk.2.ffn_gate.weight	Block 2 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
91	blk.2.ffn_up.weight	Block 2 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
92	blk.2.ffn_norm.weight	Block 2 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
93	blk.2.attn_k.weight	Block 2 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
94	blk.2.attn_output.weight	Block 2 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
95	blk.2.attn_q.weight	Block 2 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
96	blk.2.attn_v.weight	Block 2 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
97	blk.3.attn_norm.weight	Block 3 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
98	blk.3.ffn_down.weight	Block 3 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
99	blk.3.ffn_gate.weight	Block 3 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
100	blk.3.ffn_up.weight	Block 3 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
101	blk.3.ffn_norm.weight	Block 3 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
102	blk.3.attn_k.weight	Block 3 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
103	blk.3.attn_output.weight	Block 3 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
104	blk.3.attn_q.weight	Block 3 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
105	blk.3.attn_v.weight	Block 3 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
106	blk.4.attn_norm.weight	Block 4 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
107	blk.4.ffn_down.weight	Block 4 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
108	blk.4.ffn_gate.weight	Block 4 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
109	blk.4.ffn_up.weight	Block 4 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
110	blk.4.ffn_norm.weight	Block 4 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
111	blk.4.attn_k.weight	Block 4 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
112	blk.4.attn_output.weight	Block 4 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
113	blk.4.attn_q.weight	Block 4 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
114	blk.4.attn_v.weight	Block 4 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
115	blk.5.attn_norm.weight	Block 5 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
116	blk.5.ffn_down.weight	Block 5 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
117	blk.5.ffn_gate.weight	Block 5 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
118	blk.5.ffn_up.weight	Block 5 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
119	blk.5.ffn_norm.weight	Block 5 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
120	blk.5.attn_k.weight	Block 5 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
121	blk.5.attn_output.weight	Block 5 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
122	blk.5.attn_q.weight	Block 5 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
123	blk.5.attn_v.weight	Block 5 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
124	blk.6.attn_norm.weight	Block 6 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
125	blk.6.ffn_down.weight	Block 6 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
126	blk.6.ffn_gate.weight	Block 6 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
127	blk.6.ffn_up.weight	Block 6 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
128	blk.6.ffn_norm.weight	Block 6 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
129	blk.6.attn_k.weight	Block 6 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
130	blk.6.attn_output.weight	Block 6 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
131	blk.6.attn_q.weight	Block 6 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
132	blk.6.attn_v.weight	Block 6 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
133	blk.7.attn_norm.weight	Block 7 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
134	blk.7.ffn_down.weight	Block 7 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
135	blk.7.ffn_gate.weight	Block 7 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
136	blk.7.ffn_up.weight	Block 7 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
137	blk.7.ffn_norm.weight	Block 7 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
138	blk.7.attn_k.weight	Block 7 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
139	blk.7.attn_output.weight	Block 7 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
140	blk.7.attn_q.weight	Block 7 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
141	blk.7.attn_v.weight	Block 7 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
142	blk.8.attn_norm.weight	Block 8 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
143	blk.8.ffn_down.weight	Block 8 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
144	blk.8.ffn_gate.weight	Block 8 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
145	blk.8.ffn_up.weight	Block 8 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
146	blk.8.ffn_norm.weight	Block 8 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
147	blk.8.attn_k.weight	Block 8 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
148	blk.8.attn_output.weight	Block 8 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
149	blk.8.attn_q.weight	Block 8 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
150	blk.8.attn_v.weight	Block 8 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
151	blk.9.attn_norm.weight	Block 9 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
152	blk.9.ffn_down.weight	Block 9 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
153	blk.9.ffn_gate.weight	Block 9 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
154	blk.9.ffn_up.weight	Block 9 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
155	blk.9.ffn_norm.weight	Block 9 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
156	blk.9.attn_k.weight	Block 9 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
157	blk.9.attn_output.weight	Block 9 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
158	blk.9.attn_q.weight	Block 9 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
159	blk.9.attn_v.weight	Block 9 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• Total elements in blk.9: (~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
165	blk.18.attn_norm.weight	Block 18 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
166	blk.18.ffn_down.weight	Block 18 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
167	blk.18.ffn_gate.weight	Block 18 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
168	blk.18.ffn_up.weight	Block 18 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
169	blk.18.ffn_norm.weight	Block 18 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
170	blk.18.attn_k.weight	Block 18 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
171	blk.18.attn_output.weight	Block 18 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
172	blk.18.attn_q.weight	Block 18 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
173	blk.18.attn_v.weight	Block 18 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
174	blk.19.attn_norm.weight	Block 19 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
175	blk.19.ffn_down.weight	Block 19 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
176	blk.19.ffn_gate.weight	Block 19 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
177	blk.19.ffn_up.weight	Block 19 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
178	blk.19.ffn_norm.weight	Block 19 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
179	blk.19.attn_k.weight	Block 19 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
180	blk.19.attn_output.weight	Block 19 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
181	blk.19.attn_q.weight	Block 19 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
182	blk.19.attn_v.weight	Block 19 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
183	blk.20.attn_norm.weight	Block 20 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
184	blk.20.ffn_down.weight	Block 20 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
185	blk.20.ffn_gate.weight	Block 20 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
186	blk.20.ffn_up.weight	Block 20 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
187	blk.20.ffn_norm.weight	Block 20 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
188	blk.20.attn_k.weight	Block 20 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
189	blk.20.attn_output.weight	Block 20 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
190	blk.20.attn_q.weight	Block 20 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
191	blk.20.attn_v.weight	Block 20 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
192	blk.21.attn_norm.weight	Block 21 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
193	blk.21.ffn_down.weight	Block 21 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
194	blk.21.ffn_gate.weight	Block 21 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
195	blk.21.ffn_up.weight	Block 21 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
196	blk.21.ffn_norm.weight	Block 21 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
197	blk.21.attn_k.weight	Block 21 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
198	blk.21.attn_output.weight	Block 21 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
199	blk.21.attn_q.weight	Block 21 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
200	blk.21.attn_v.weight	Block 21 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
201	blk.22.attn_norm.weight	Block 22 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
202	blk.22.ffn_down.weight	Block 22 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
203	blk.22.ffn_gate.weight	Block 22 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
204	blk.22.ffn_up.weight	Block 22 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
205	blk.22.ffn_norm.weight	Block 22 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
206	blk.22.attn_k.weight	Block 22 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
207	blk.22.attn_output.weight	Block 22 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
208	blk.22.attn_q.weight	Block 22 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
209	blk.22.attn_v.weight	Block 22 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
210	blk.23.attn_norm.weight	Block 23 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
211	blk.23.ffn_down.weight	Block 23 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
212	blk.23.ffn_gate.weight	Block 23 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
213	blk.23.ffn_up.weight	Block 23 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
214	blk.23.ffn_norm.weight	Block 23 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
215	blk.23.attn_k.weight	Block 23 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
216	blk.23.attn_output.weight	Block 23 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
217	blk.23.attn_q.weight	Block 23 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
218	blk.23.attn_v.weight	Block 23 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
219	blk.24.attn_norm.weight	Block 24 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
220	blk.24.ffn_down.weight	Block 24 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
221	blk.24.ffn_gate.weight	Block 24 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
222	blk.24.ffn_up.weight	Block 24 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
223	blk.24.ffn_norm.weight	Block 24 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
224	blk.24.attn_k.weight	Block 24 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
225	blk.24.attn_output.weight	Block 24 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
226	blk.24.attn_q.weight	Block 24 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
227	blk.24.attn_v.weight	Block 24 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
228	blk.25.attn_norm.weight	Block 25 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
229	blk.25.ffn_down.weight	Block 25 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
230	blk.25.ffn_gate.weight	Block 25 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
231	blk.25.ffn_up.weight	Block 25 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
232	blk.25.ffn_norm.weight	Block 25 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
233	blk.25.attn_k.weight	Block 25 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
234	blk.25.attn_output.weight	Block 25 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
235	blk.25.attn_q.weight	Block 25 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
236	blk.25.attn_v.weight	Block 25 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
237	blk.26.attn_norm.weight	Block 26 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
238	blk.26.ffn_down.weight	Block 26 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
239	blk.26.ffn_gate.weight	Block 26 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
240	blk.26.ffn_up.weight	Block 26 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
241	blk.26.ffn_norm.weight	Block 26 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
242	blk.26.attn_k.weight	Block 26 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
243	blk.26.attn_output.weight	Block 26 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
244	blk.26.attn_q.weight	Block 26 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
245	blk.26.attn_v.weight	Block 26 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
246	blk.27.attn_norm.weight	Block 27 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
247	blk.27.ffn_down.weight	Block 27 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
248	blk.27.ffn_gate.weight	Block 27 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
249	blk.27.ffn_up.weight	Block 27 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
250	blk.27.ffn_norm.weight	Block 27 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
251	blk.27.attn_k.weight	Block 27 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
252	blk.27.attn_output.weight	Block 27 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
253	blk.27.attn_q.weight	Block 27 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
254	blk.27.attn_v.weight	Block 27 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
255	blk.28.attn_norm.weight	Block 28 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
256	blk.28.ffn_down.weight	Block 28 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
257	blk.28.ffn_gate.weight	Block 28 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
258	blk.28.ffn_up.weight	Block 28 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
259	blk.28.ffn_norm.weight	Block 28 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
260	blk.28.attn_k.weight	Block 28 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
261	blk.28.attn_output.weight	Block 28 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
262	blk.28.attn_q.weight	Block 28 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
263	blk.28.attn_v.weight	Block 28 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
264	blk.29.attn_norm.weight	Block 29 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
265	blk.29.ffn_down.weight	Block 29 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
266	blk.29.ffn_gate.weight	Block 29 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
267	blk.29.ffn_up.weight	Block 29 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
268	blk.29.ffn_norm.weight	Block 29 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
269	blk.29.attn_k.weight	Block 29 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
270	blk.29.attn_output.weight	Block 29 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
271	blk.29.attn_q.weight	Block 29 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
272	blk.29.attn_v.weight	Block 29 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
273	blk.30.attn_norm.weight	Block 30 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
274	blk.30.ffn_down.weight	Block 30 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
275	blk.30.ffn_gate.weight	Block 30 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
276	blk.30.ffn_up.weight	Block 30 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
277	blk.30.ffn_norm.weight	Block 30 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
278	blk.30.attn_k.weight	Block 30 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
279	blk.30.attn_output.weight	Block 30 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
280	blk.30.attn_q.weight	Block 30 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
281	blk.30.attn_v.weight	Block 30 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

• 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
282	blk.31.attn_norm.weight	Block 31 Attention Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
283	blk.31.ffn_down.weight	Block 31 Feed-Forward Network "Down" (W)	(~59M) 58720256	14336 x 4096 x 1 x 1	F16
284	blk.31.ffn_gate.weight	Block 31 Feed-Forward Network "Gate" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
285	blk.31.ffn_up.weight	Block 31 Feed-Forward Network "Up" (W)	(~59M) 58720256	4096 x 14336 x 1 x 1	F16
286	blk.31.ffn_norm.weight	Block 31 Feed-Forward Network Normalization (W)	( ~4K) 4096	4096 x 1 x 1 x 1	F32
287	blk.31.attn_k.weight	Block 31 Attention Key (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16
288	blk.31.attn_output.weight	Block 31 Attention Output (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
289	blk.31.attn_q.weight	Block 31 Attention Query (W)	(~17M) 16777216	4096 x 4096 x 1 x 1	F16
290	blk.31.attn_v.weight	Block 31 Attention Value (W)	( ~4M) 4194304	4096 x 1024 x 1 x 1	F16

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