Commit Graph
10 Commits
Author SHA1 Message Date
Will LinandClaude Fable 5 9713ea1275 [misc] use the full release name FastVideo-Minimax-FastH3-Preview-v0.1
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-21 09:27:38 +00:00
Will LinandClaude Fable 5 3f00983287 [feat] attention: opt-in sm_100a CUDA forward route for VSA-H3 tile-64
FASTVIDEO_VSA_SM100A=1 (default off) sends no-grad tile-64 forwards through
fastvideo_kernel.block_sparse_attn_sm100a (the Blackwell block-sparse
forward merged in #1719, which handles per-q-tile NON-uniform q2k_num rows
and zero-count rows). Route preconditions: module importable,
is_supported() (sm_100 device, bf16, head_dim 128, even tile count), no
grad tracking; any failure with the env set logs one warning and falls
back to the Triton-64 kernels, which also keep the entire grad path
unchanged.

The bool block map is compacted with the same map_to_index the Triton bool
entry uses, so the sm_100a kernel sees H3's true NON-uniform per-row counts
(prefix query tiles dense, video tiles prefix+top-k).

The FastH3 example surfaces the route as --vsa-kernel {triton,sm100a}
(default triton), which sets the env before pipeline boot so spawned GPU
workers inherit it; documented in the basic README.

CPU route-selection tests: default-off, engage-on-env, grad fallback,
warn-once fallback for missing module/unsupported geometry, no-grad-context
detection.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-21 09:27:38 +00:00
Will LinandClaude Fable 5 2dc57f4070 [misc] rebrand the few-step preview to FastH3 (model string, example name, docs)
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-21 09:27:38 +00:00
Will LinandClaude Fable 5 9df19be719 [feat] example: few-step FastVideo-Minimax-H3-Preview inference (4-step DMD2 student)
basic_fast_minimax_h3.py runs FastVideo/FastVideo-Minimax-H3-Preview-v0.1,
the data-free-DMD2 distillation of MiniMax-H3: 4 denoising steps on the
release sampler's shift-12 schedule (vs the base model's 50), synchronized
video+audio in one pipeline call, guidance_scale 1.0.

The script always requests the VSA-H3 attention backend through the typed
boot-time route (pipeline.experimental -> FastVideoArgs.attention_backend):
the student checkpoint carries trained to_gate_compress gates, which only
exist under that backend. --vsa-sparsity defaults to 0.0 (every tile
selected — exactly dense attention); --vsa-tile-size defaults to 64, the
geometry the student was trained with, and is forwarded even at sparsity 0
because the gate-compress branch pools per tile. The HF repo is private
while the MiniMax H3 Community License review completes; --model-path
accepts a local snapshot meanwhile (noted in the script and README).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-21 09:27:38 +00:00
William Lin c591d6d2a6 [feat] [2/n] Improve API: add initial support in video_generator (#1220) 2026-04-06 10:33:54 -07:00
Loay Rashid e53730f324 [docs] Minor Fixes (#942) 2025-12-19 16:48:16 -06:00
Yongqi ChenandSolitaryThinker 4264a80ca9 [Feature] Add DMD inference pipeline (#637)
Co-authored-by: SolitaryThinker <wlsaidhi@gmail.com>
2025-07-24 21:00:47 -07:00
William Lin 0cf001986a [Docs] More docs update (#394) 2025-05-11 16:19:47 -07:00
William Lin c69afce2f6 [Docs] Update for V1 (#381) 2025-05-06 16:34:44 -07:00
William Lin 2bf69b6f92 [Docs] Initial examples setup and more docs (#332) 2025-04-14 16:53:57 -07:00