pth listlengths 3 3 | __key__ stringlengths 17 21 | __url__ stringclasses 1
value |
|---|---|---|
[{"context":null,"input_latents":[[[[[0.6015625,0.74609375,0.71484375,0.671875,0.69921875,0.6171875,(...TRUNCATED) | cache_v23_rev/0/11547 | hf://datasets/hz6666/cad-video-cache@b193f3f33f1c7f909980095b50855f74be779272/cache_v23_rev.tar |
[{"context":null,"input_latents":[[[[[0.59375,0.73828125,0.71484375,0.6328125,0.578125,0.58203125,0.(...TRUNCATED) | cache_v23_rev/0/4292 | hf://datasets/hz6666/cad-video-cache@b193f3f33f1c7f909980095b50855f74be779272/cache_v23_rev.tar |
[{"context":null,"input_latents":[[[[[0.59765625,0.74609375,0.7109375,0.6484375,0.69140625,0.6210937(...TRUNCATED) | cache_v23_rev/0/3834 | hf://datasets/hz6666/cad-video-cache@b193f3f33f1c7f909980095b50855f74be779272/cache_v23_rev.tar |
[{"context":null,"input_latents":[[[[[0.60546875,0.73828125,0.6953125,0.59375,0.60546875,0.67578125,(...TRUNCATED) | cache_v23_rev/0/3963 | hf://datasets/hz6666/cad-video-cache@b193f3f33f1c7f909980095b50855f74be779272/cache_v23_rev.tar |
[{"context":null,"input_latents":[[[[[0.59765625,0.74609375,0.72265625,0.66796875,0.6953125,0.597656(...TRUNCATED) | cache_v23_rev/0/6795 | hf://datasets/hz6666/cad-video-cache@b193f3f33f1c7f909980095b50855f74be779272/cache_v23_rev.tar |
[{"context":null,"input_latents":[[[[[0.59765625,0.74609375,0.7109375,0.6484375,0.6953125,0.62109375(...TRUNCATED) | cache_v23_rev/0/3900 | hf://datasets/hz6666/cad-video-cache@b193f3f33f1c7f909980095b50855f74be779272/cache_v23_rev.tar |
[{"context":null,"input_latents":[[[[[0.6015625,0.74609375,0.69921875,0.67578125,0.6875,0.5859375,0.(...TRUNCATED) | cache_v23_rev/0/3074 | hf://datasets/hz6666/cad-video-cache@b193f3f33f1c7f909980095b50855f74be779272/cache_v23_rev.tar |
[{"context":null,"input_latents":[[[[[0.59375,0.73828125,0.71484375,0.63671875,0.58203125,0.56640625(...TRUNCATED) | cache_v23_rev/0/1674 | hf://datasets/hz6666/cad-video-cache@b193f3f33f1c7f909980095b50855f74be779272/cache_v23_rev.tar |
[{"context":null,"input_latents":[[[[[0.60546875,0.734375,0.734375,0.671875,0.7109375,0.6171875,0.72(...TRUNCATED) | cache_v23_rev/0/5322 | hf://datasets/hz6666/cad-video-cache@b193f3f33f1c7f909980095b50855f74be779272/cache_v23_rev.tar |
[{"context":null,"input_latents":[[[[[0.59375,0.74609375,0.72265625,0.67578125,0.703125,0.62109375,0(...TRUNCATED) | cache_v23_rev/0/3549 | hf://datasets/hz6666/cad-video-cache@b193f3f33f1c7f909980095b50855f74be779272/cache_v23_rev.tar |
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
cad-video-cache — pre-encoded latent caches (skip data_process)
Slimmed VAE+T5 latent caches for the CAD video world-model (cad_video_gen). Download +
extract a tar to skip the ~8-9h data_process, then train directly:
train_df.py --dataset_base_path cache_xxx.
What's in a .pth
Each clip is one file cache_*/0/{idx}.pth (~1.3 MB), a 2-tuple of dicts:
[0]["input_latents"]— Wan-VAE video latent(1, 16, T, 60, 60)bf16: 16 channels, T temporal-latent frames (VAE 4:1 causal), 60x60 = 480/8 spatial. T=7 -> 25 pixel frames, T=5 -> 17 pixel frames.[1]["context"]— T5-XXL text embedding(1, 64, 4096)(slim keeps the first 64 tokens).
⚠️ recipe-bound: a cache is reusable ONLY for the same (frames, resolution, reverse, slim) recipe it was built with — a different num_frames / resolution needs a fresh data_process.
Caches & their provenance
| tar | status | pth | frames | source dataset | pipeline | use |
|---|---|---|---|---|---|---|
cache_xycanon25_rev.tar |
available | 16670 | 25f (latent T=7) | xycanon — canonical 5-view (3334 parts x 5 views) | xycanon clips -> make_vace_dataset (atomic_xycanon_vace25) -> reverse_videos -> data_process | 25f flagship exp2_df_xy25_rev (LPIPS 0.298) + the frozen-backbone memory for all op-decoders |
cache_v23_rev.tar |
available | 11748 | 17f (latent T=5) | v2+v3 — curated 11748-uid set, iso-view (v00) | fetch v00 clips -> make_vace -> reverse -> data_process | 17f base line / legacy op-decoder |
cache_xycanon_rev.tar |
available | 10201 | 17f (latent T=5) | xycanon — earlier subset (pre-25f line) | xycanon clips -> make_vace -> reverse -> data_process | early 17f xycanon experiments |
cache_v2v3xy25_rev.tar |
available | ~34938 | 25f (latent T=7) | v2+v3+xy merged, no-view prompts (18268 v23 + 16670 xy) | merge symlinks -> reverse -> data_process | the new no-view v2v3+xy video base |
Common to all: 480x480, reverse (target rendered at frame 0), slim (only
input_latents + context[:64]), bf16. Raw sources live in hz6666/3d-wm-atomic-{v2,v3}
(WebDataset shards) and the xycanon repo; the rebuild recipe is data_backup.md in cad_video_gen.
Extract: tar -xf cache_xycanon25_rev.tar -> cache_xycanon25_rev/. Full live asset map +
lineage diagram: docs/data_inventory.md in the cad_video_gen repo.
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