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HY-Video-Avatar2 checkpoints

This repository contains experimental WanModelAudio transformer checkpoints for HY-Video-Avatar2.

Checkpoints

Directory	Description inferred from run name
`1229_fsdp_high_ct2_4800`	High-noise CT2 checkpoint
`0104_fsdp_low_ct2_600`	Low-noise CT2 checkpoint
`0115_fs3_emo_1_2600`	Emotion-focused checkpoint
`0120_fs10_motion_6_1200`	Motion-focused checkpoint
`0128_fs10_balanced_4_600`	Balanced checkpoint
`0129_fs3_balanced_1_1200`	Balanced checkpoint
`0202/ckpt/high_model`	High-noise model checkpoint
`0202/ckpt/low_model`	Distilled low-noise model checkpoint

Each checkpoint directory contains:

config.json: WanModelAudio architecture configuration.
diffusion_pytorch_model.safetensors: transformer weights.

Loading

Use the custom WanModelAudio implementation from the HY-Video-Avatar2 codebase and point from_pretrained at one checkpoint directory, for example:

from infer.wan.modules.model_audio import WanModelAudio

model = WanModelAudio.from_pretrained(
    "bigfacing/HY-Video-Avatar2",
    subfolder="0129_fs3_balanced_1_1200",
)

These are transformer-only checkpoints; the remaining inference components and configuration must be supplied by the HY-Video-Avatar2 codebase.

Notes

Checkpoint names are preserved from the original training runs for reproducibility.
The descriptions above are inferred from those run names.
Intended for research use; evaluate outputs, identity handling, consent, and applicable rights before deployment.

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