Video-to-Video
PEFT
Safetensors
Wan2.2
English
Chinese
wan-fun
controlnet
depth-control
lora
dmd
non-ar
four-step
cfg-free
cfg1
train-cfg4
rgs3
step1600
rank64
Instructions to use Perflow-Shuai/WAN-Fun-LoRA-5B-Control-TrainCFG4-4Step-CFG1-step1600 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Perflow-Shuai/WAN-Fun-LoRA-5B-Control-TrainCFG4-4Step-CFG1-step1600 with PEFT:
Task type is invalid.
- Wan2.2
How to use Perflow-Shuai/WAN-Fun-LoRA-5B-Control-TrainCFG4-4Step-CFG1-step1600 with Wan2.2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| # Training configuration; local asset paths normalized for publication. | |
| # model_name selects shared VAE/text assets; fun_control_model_path selects the trained DiT. | |
| infra: | |
| expected_world_size: 16 | |
| expected_nodes: 2 | |
| expected_gpus_per_node: 8 | |
| required_gpu_name: H100 | |
| sharding_strategy: hybrid_full | |
| mixed_precision: true | |
| vae_dtype: float32 | |
| gradient_checkpointing: true | |
| generator_fsdp_wrap_strategy: size | |
| real_score_fsdp_wrap_strategy: size | |
| fake_score_fsdp_wrap_strategy: size | |
| text_encoder_fsdp_wrap_strategy: size | |
| model_kwargs: | |
| model_name: Wan2.2-TI2V-5B | |
| fun_control_model_path: models/Wan2.2-Fun-5B-Control | |
| timestep_shift: 5.0 | |
| num_frame_per_block: 8 | |
| local_attn_size: -1 | |
| control_raw_frames: 93 | |
| checkpoints: | |
| generator_ckpt: null | |
| real_score_ckpt: null | |
| fake_score_ckpt: null | |
| algorithm: | |
| trainer: score_distillation | |
| distribution_loss: dmd | |
| generator_is_causal: false | |
| real_score_is_causal: false | |
| fake_score_is_causal: false | |
| all_causal: false | |
| backward_simulation: true | |
| independent_first_frame: false | |
| ts_schedule: false | |
| real_guidance_scale: 3.0 | |
| fake_guidance_scale: 0.0 | |
| training: | |
| lr: 1.0e-05 | |
| lr_critic: 2.0e-06 | |
| weight_decay: 0.0 | |
| beta1: 0.0 | |
| beta2: 0.999 | |
| beta1_critic: 0.0 | |
| beta2_critic: 0.999 | |
| batch_size: 1 | |
| gradient_accumulation_steps: 2 | |
| ema_weight: 0.99 | |
| ema_start_step: 200 | |
| log_iters: 100 | |
| max_checkpoints: 20 | |
| max_iters: 3000 | |
| gc_interval: 100 | |
| dfake_gen_update_ratio: 5 | |
| min_num_training_frames: 24 | |
| num_training_frames: 24 | |
| slice_last_frames: 24 | |
| data: | |
| data_path: data/depth_video_5k/manifest.jsonl | |
| eval_data_path: data/depth_video_5k/manifest.jsonl | |
| control_manifest: data/depth_video_5k/manifest.jsonl | |
| eval_control_manifest: data/depth_video_5k/manifest.jsonl | |
| control_raw_frames: 93 | |
| control_min_temporal_difference: 0.0001 | |
| control_num_workers: 2 | |
| image_or_video_shape: | |
| - 1 | |
| - 24 | |
| - 48 | |
| - 30 | |
| - 52 | |
| full_ref_mode: zero_through_ref_conv | |
| inference: | |
| sampling_steps: 4 | |
| guidance_scale: 1.0 | |
| inference_guidance_scale: 1.0 | |
| sink_size: 0 | |
| multi_shot_rope_offset: 0 | |
| evaluation: | |
| interval: -1 | |
| num_frames: 24 | |
| use_ema: false | |
| val_batch_size: 1 | |
| save_latents_only: true | |
| adapter: | |
| type: lora | |
| rank: 64 | |
| alpha: 64 | |
| dropout: 0.0 | |
| apply_to_critic: true | |
| verbose: false | |
| logging: | |
| seed: 17 | |
| wandb_entity: null | |
| wandb_project: LongLive-WanFun5B-Control-DMD | |