File size: 4,586 Bytes
3ee8a95
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
{
  "reference_materials": {
    "OpenGVLab--InternVL3-1B__config.json": {
      "repo": "OpenGVLab/InternVL3-1B",
      "revision": "4415a3b810e636d11dfa86b0e9ba40bb00535aa8",
      "file": "config.json",
      "url": "https://huggingface.co/OpenGVLab/InternVL3-1B/resolve/4415a3b810e636d11dfa86b0e9ba40bb00535aa8/config.json",
      "sha256": "8a252be385dbef3abf1c58d028ea5116849a33dc7a1601c350c3ee28f202524c"
    },
    "OpenGVLab--InternVL3-1B__modeling_intern_vit.py": {
      "repo": "OpenGVLab/InternVL3-1B",
      "revision": "4415a3b810e636d11dfa86b0e9ba40bb00535aa8",
      "file": "modeling_intern_vit.py",
      "url": "https://huggingface.co/OpenGVLab/InternVL3-1B/resolve/4415a3b810e636d11dfa86b0e9ba40bb00535aa8/modeling_intern_vit.py",
      "sha256": "d3e0f68f29e86be1f3e6e101dc45303ec24e5115e0034de101665972576eb348"
    },
    "OpenGVLab--InternVL3-1B__configuration_intern_vit.py": {
      "repo": "OpenGVLab/InternVL3-1B",
      "revision": "4415a3b810e636d11dfa86b0e9ba40bb00535aa8",
      "file": "configuration_intern_vit.py",
      "url": "https://huggingface.co/OpenGVLab/InternVL3-1B/resolve/4415a3b810e636d11dfa86b0e9ba40bb00535aa8/configuration_intern_vit.py",
      "sha256": "22dd687a5f142985407675fc6b1dc688c2ded93e54192543ecf28ef495a6efa8"
    },
    "OpenGVLab--InternVL3-1B-hf__config.json": {
      "repo": "OpenGVLab/InternVL3-1B-hf",
      "revision": "014c0583a0d4bedf29fbe2dbff4f865eb998e171",
      "file": "config.json",
      "url": "https://huggingface.co/OpenGVLab/InternVL3-1B-hf/resolve/014c0583a0d4bedf29fbe2dbff4f865eb998e171/config.json",
      "sha256": "7dd610d98f11ea7d37f5086a990eca7df22f0b5d7a36c5dbf41d060b97bdf901"
    },
    "Efficient-Large-Model--Sana_600M_512px_diffusers__transformer__config.json": {
      "repo": "Efficient-Large-Model/Sana_600M_512px_diffusers",
      "revision": "83d7a190bfd1fd070570a793d2dab5c7a3231b9d",
      "file": "transformer/config.json",
      "url": "https://huggingface.co/Efficient-Large-Model/Sana_600M_512px_diffusers/resolve/83d7a190bfd1fd070570a793d2dab5c7a3231b9d/transformer/config.json",
      "sha256": "44dfc5f16b396035371d4b5a56ef3773a9be9e0c679337b0336b2b81b78be3b8"
    },
    "Efficient-Large-Model--Sana_600M_512px_diffusers__vae__config.json": {
      "repo": "Efficient-Large-Model/Sana_600M_512px_diffusers",
      "revision": "83d7a190bfd1fd070570a793d2dab5c7a3231b9d",
      "file": "vae/config.json",
      "url": "https://huggingface.co/Efficient-Large-Model/Sana_600M_512px_diffusers/resolve/83d7a190bfd1fd070570a793d2dab5c7a3231b9d/vae/config.json",
      "sha256": "4e5669aa03caa77615b73b21c9347c384cb11124a9590683e32a510df0176eb4"
    },
    "Efficient-Large-Model--Sana_600M_512px_diffusers__scheduler__scheduler_config.json": {
      "repo": "Efficient-Large-Model/Sana_600M_512px_diffusers",
      "revision": "83d7a190bfd1fd070570a793d2dab5c7a3231b9d",
      "file": "scheduler/scheduler_config.json",
      "url": "https://huggingface.co/Efficient-Large-Model/Sana_600M_512px_diffusers/resolve/83d7a190bfd1fd070570a793d2dab5c7a3231b9d/scheduler/scheduler_config.json",
      "sha256": "70e8603120cc387316aa3bc7f08cb2872f6b6eb6eff6f25df1b88b6b76389e81"
    },
    "mit-han-lab--dc-ae-f32c32-sana-1.1-diffusers__config.json": {
      "repo": "mit-han-lab/dc-ae-f32c32-sana-1.1-diffusers",
      "revision": "6f7b3f3b289a439a11ef4fb1034989fd4b9a4766",
      "file": "config.json",
      "url": "https://huggingface.co/mit-han-lab/dc-ae-f32c32-sana-1.1-diffusers/resolve/6f7b3f3b289a439a11ef4fb1034989fd4b9a4766/config.json",
      "sha256": "d448e075595d708140d53102b3e21362845ffdfcf5c62638256fe37559c55c34"
    }
  },
  "external_decoder": {
    "url": "https://raw.githubusercontent.com/nnnth/UniLIP/937ee73991d68e1a53c1ac156e1a62e6b251e6aa/unilip/model/vae_modules.py",
    "sha256": "5666de0ad561036d5206583881a81367502ee7f8628ae67dae9fb022b521838a",
    "included": false,
    "reason": "The official code repository has no root license; do not redistribute this file. Supply a local official checkout explicitly to the loader."
  },
  "local_loader": "Independent packaging glue; uses the original trained tensor names and licensed constructors.",
  "changes": [
    "InternVision configuration disables optional FlashAttention for CPU; native attention equations retained.",
    "DC-AE from_pretrained constructor is replaced with config-only meta construction inside a scoped patch; strict loading subsequently supplies every trained decoder tensor.",
    "Qwen connector keeps the original final six layers and removes its unused token embedding."
  ]
}