Add stage 1/2/3 checkpoints, config.json, and model card

a9a7638 verified 24 days ago

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license: apache-2.0
datasets:
  - KlingTeam/MultiCamVideo-Dataset
  - KlingTeam/SynCamVideo-Dataset
base_model:
  - alibaba-pai/Wan2.1-Fun-V1.1-1.3B-Control-Camera
base_model_relation: finetune
pipeline_tag: video-to-video
tags:
  - pytorch

This model was presented in FlashRender: Few-Step Generative Rendering via Camera-Controlled Video MeanFlow.

Please refer to the Github README for usage.

Checkpoints

Stage	File	Sampling
1	`epoch_20.safetensors`	50 steps, `inference_mode=mul`
2	`meanflow_epoch_20.safetensors`	4 steps, `inference_mode=any`
3	`onpolicy_epoch_5.safetensors`	4 steps, `inference_mode=any`

onpolicy_epoch_5.safetensors is the final model and the default in configs/base.yaml.

Each file stores only the trainable parameter subset, not a stand-alone diffusers/transformers checkpoint. Weights are bfloat16, except the relative-pose tokens and the per-block RoPE phase MLPs (rel_pose_{src,tgt}_token, self_attn.rope_phase_{qk,vo}), which are stored in float32. They are loaded with strict=False onto the base Wan DiT after it is patched by flashrender_utils.model_utils.adjust_to_FlashRender, so use the code repository:

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="byeongjun-park/FlashRender",
    local_dir="models/checkpoints",
    allow_patterns=["*.safetensors", "config.json"],
)