Self Forcing (autoregressive streaming video diffusion)
Source: https://github.com/guandeh17/self-forcing
Structured fields
{
"archived": false,
"checked_at": "2026-10-17T00:00:00.000Z",
"usefulness": "Training method that rolls out autoregressively with KV caching during training to cut train/inference mismatch, claiming real-time streaming generation on one RTX 4090 from a Wan2.1-1.3B base. Foundation for several long-video and interactive-video lines.",
"source_type": "repository",
"availability": "available",
"dependencies": [
"Wan2.1-T2V-1.3B",
"CausVid lineage"
],
"source_owner": "guandeh17",
"next_check_at": "2026-10-31T00:00:00.000Z",
"hardware_notes": "Upstream: Linux, Nvidia GPU >= 24 GB (RTX 4090, A100, H100 tested), 64 GB RAM.",
"known_limitations": [
"Real-time claim is upstream's, not reproduced.",
"Other hardware untested per README."
],
"upstream_updated_at": "2025-09-12T03:31:30.000Z"
}Evidence claims
- [upstream_claim] README claims real-time streaming video generation on a single RTX 4090 with quality matching state-of-the-art diffusion models; NeurIPS 2025 Spotlight; needs >= 24 GB GPU and 64 GB RAM; base Wan2.1-T2V-1.3B. source
- [upstream_claim] README: DMD training run is 600 iterations, under 2 hours on 64 H100 GPUs; torch.compile, TAEHV-VAE and FP8 linear suggested for speed with possible quality loss. source
- [upstream_claim] HF model card lists Apache-2.0 and cites arXiv 2506.08009. source
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| code | Apache-2.0 | permitted | permitted | permitted | unknown | README states code is Apache-2.0. |
| model_weights | Apache-2.0 | permitted | permitted | permitted | unknown | HF metadata Apache-2.0; derived from Wan2.1 1.3B (separate Apache-2.0 per Wan README); GitHub page does not state weights license. |