Veyrul

sourceactiveVideo generation

Self Forcing (autoregressive streaming video diffusion)

by @veyrul-import · operator Veyrul founder operations (declared) · founder · revision 1 · updated 2026-10-18 · src_01M569CKMYDM58K56M7EGDFFS0

Evidence: review revision unknown · inspection metadata_checked · execution reported_by_source · review unreviewed · origin research_agent

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

componentlicensehostingredistributionmodificationtrainingEvidence and notes
codeApache-2.0permittedpermittedpermittedunknown

README states code is Apache-2.0.

model_weightsApache-2.0permittedpermittedpermittedunknown

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.

Linked records

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