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hao-ai-lab-FastVideo/examples
SolitaryThinker d6e020402e [feat] magi-human: switch all 8 examples to umbrella HF repo + register umbrella paths
Phase 5: with all 4 weight variants now uploaded under
FastVideo/MagiHuman-Diffusers (one HF repo, four sibling subfolders
base / distill / sr_540p / sr_1080p), all magi-human examples now
default to the umbrella string. Local conversion via the
checkpoint_conversion script remains supported and is documented in
the example docstrings.

Files updated:
  * basic_magi_human.py:                      base T2V    -> base
  * basic_magi_human_ti2v.py:                 base TI2V   -> base
  * basic_magi_human_distill.py:              distill T2V -> distill
  * basic_magi_human_distill_ti2v.py:         distill TI2V-> distill
  * basic_magi_human_sr540p.py:               sr-540p T2V -> sr_540p
  * basic_magi_human_sr540p_ti2v.py:          sr-540p TI2V-> sr_540p
  * basic_magi_human_sr1080p.py:              sr-1080p T2V-> sr_1080p
  * basic_magi_human_sr1080p_ti2v.py:         sr-1080p TI2V-> sr_1080p

  * fastvideo/registry.py: hf_model_paths for the base T2V config now
    includes 'FastVideo/MagiHuman-Diffusers/base' and the distill T2V
    config includes 'FastVideo/MagiHuman-Diffusers/distill', alongside
    the existing per-variant repo names. The SR umbrella paths
    (sr_540p / sr_1080p) were already registered by Phases 3/4. TI2V
    variants reuse the same weight subfolders and are selected at
    load time via override_pipeline_cls_name + pipeline_config (see
    basic_magi_human_ti2v.py for the pattern).

Verified end-to-end:
  * pytest tests/local_tests/magi_human/ -v -s: 14 passed, 0 failed.
    All bit-exact (diff_max=0.0, diff_mean=0.0).
  * basic_magi_human.py with local converted_weights/magi_human_base
    moved out, forcing snapshot_download from the umbrella repo:
    mp4 byte-identical md5 dcf5f2bf6534c7c0d91e7353e42b23db (matches
    pre-upload local-path output exactly).

Notes:
  * fastvideo/utils.py:maybe_download_model already supports the
    'org/repo/subfolder' umbrella form (committed in e2ef3234), and
    fastvideo/pipelines/basic/magi_human/magi_human_pipeline.py
    lazy-loads the four shared components (Wan VAE, T5-Gemma encoder
    + tokenizer, Stable Audio VAE) from their canonical upstream HF
    repos so each umbrella subfolder only ships transformer/ +
    scheduler/ + (sr_transformer/) + model_index.json.
  * Total HF Hub footprint after upload: ~165 GB raw, server-side
    deduped. User cache footprint per variant is ~5-30 GB transformer
    (+ ~30 GB sr_transformer for SR) plus a single ~25 GB upstream
    cache shared across all variants.
2026-05-05 10:55:49 -07:00
..
2026-03-09 18:58:56 -07:00