Model Information




Description
Simple WAN T2V Workflow for Self Forcing
Self Forcing trains autoregressive video diffusion models by simulating the inference process during training, performing autoregressive rollout with KV caching. It resolves the train-test distribution mismatch and enables real-time, streaming video generation on a single RTX 4090 while matching the quality of state-of-the-art diffusion models.
Download self_forcing_dmd.pt from https://huggingface.co/gdhe17/Self-Forcing/tree/main/checkpoints and use it as the t2v checkpoint.
Project website: https://self-forcing.github.io/
Self Forcing Simple WAN T2V Workflow
i2v Vace
605downloads
Download ModelModel Details
- Type
- Generic Asset
- Subtype
- Workflows
- Created
- Updated
- June 6, 2026