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yslan
/
Track4D-2026

Video-to-Video
Diffusers
video
tracking
3d
wan
Model card Files Files and versions
xet
Community

Instructions to use yslan/Track4D-2026 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use yslan/Track4D-2026 with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("yslan/Track4D-2026", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
Track4D-2026
Ctrl+K
Ctrl+K
  • 1 contributor
History: 18 commits
yslan's picture
yslan
Record experimental checkpoint hashes
f6dd8df verified 4 days ago
  • evaluation
    Add aligned Stream3R short256 49-frame evaluation NPZ assets 4 days ago
  • experimental
    Add retained experimental DA3 VDM ViT-DPT step 16K checkpoint 4 days ago
  • ncmv
    Upload NCMV Wan2.1 14B step-4000 5 days ago
  • rtv
    Upload joint RTV-NCMV Wan2.1 14B step-5000 5 days ago
  • .gitattributes
    10.2 kB
    Add exact dense 2D step 11.5K metrics NPZ and visualizations 4 days ago
  • README.md
    2.83 kB
    Document experimental checkpoints and evaluation assets 4 days ago
  • checkpoint_manifest.json
    1.89 kB
    Record experimental checkpoint hashes 4 days ago