Instructions to use Delcher/fewsteprl-wan21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Delcher/fewsteprl-wan21 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nvidia/AnyFlow-Wan2.1-T2V-1.3B-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Delcher/fewsteprl-wan21") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Download meanflowopsd/config.yaml from Delcher/fewsteprl-wan21: direct link, hf CLI and curl.
- Browser
- Download file 3.73 kB
-
https://huggingface.co/Delcher/fewsteprl-wan21/resolve/main/meanflowopsd/config.yaml
- Command line
-
hf download hf://Delcher/fewsteprl-wan21/meanflowopsd/config.yaml
-
curl -L -o config.yaml https://huggingface.co/Delcher/fewsteprl-wan21/resolve/main/meanflowopsd/config.yaml
3.73 kB
| model: | |
| pretrained_path: models/AnyFlow-Wan2.1-T2V-1.3B-Diffusers | |
| generator_init_path: '' | |
| aux_v_init_path: '' | |
| model_type: wan | |
| gradient_checkpointing: true | |
| dtype: bf16 | |
| generator_lora: | |
| enabled: true | |
| rank: 32 | |
| lora_alpha: 64 | |
| target_modules: | |
| - to_q | |
| - to_k | |
| - to_v | |
| - to_out.0 | |
| - net.0.proj | |
| - net.2 | |
| init_lora_weights: gaussian | |
| load_path: '' | |
| pre_merge_paths: [] | |
| merge_before_training: false | |
| video: | |
| num_frames: 81 | |
| eval_num_frames: 81 | |
| height: 480 | |
| width: 832 | |
| fps: 16 | |
| max_sequence_length: 512 | |
| fewstep_rl: | |
| num_epochs: 250 | |
| num_batches_per_epoch: 2 | |
| num_inner_epochs: 1 | |
| rl_inner_batch_size: 0 | |
| rl_start_epoch: 0 | |
| num_image_per_prompt: 16 | |
| rl_sample_use_ema: false | |
| sampling_num_steps: 4 | |
| sampling_guidance_scale: 1.0 | |
| per_prompt_stat_tracking: true | |
| per_prompt_global_std: true | |
| weight_advantages: true | |
| adv_clip_max: 5.0 | |
| beta: 0.1 | |
| kl_weight: 0.0001 | |
| decay_type: 1 | |
| rl_decay_interval: 1 | |
| reward_fn: | |
| hpsv3_general: 1.0 | |
| hpsv3_percentile: 1.0 | |
| videoalign_mq: 1.0 | |
| videoalign_ta: 1.0 | |
| reward_model_paths: | |
| videoalign_dir: third_party/VideoAlign | |
| videoalign_ckpt: models/VideoReward | |
| log_sample_images: 0 | |
| central_diff_epsilon: 5.0 | |
| cd_velocity_source: noise_minus_x0 | |
| share_cd_with_old: true | |
| disable_cd: true | |
| num_training_timesteps_per_sample: 4 | |
| rl_min_timestep: 0 | |
| rl_max_timestep: 1000 | |
| diffusion_ratio: 0.5 | |
| consistency_ratio: 0.25 | |
| use_ref_v_model: false | |
| guidance_scale: 1.0 | |
| rollout_type: ode | |
| clip_range: 0.001 | |
| reuse_x_t: false | |
| aux_v_enabled: false | |
| max_aux_sample: 0 | |
| renoise_per_epoch: 10 | |
| aux_v_gradient_accum: 1 | |
| aux_v_batch_size: 0 | |
| opsd_enabled: true | |
| opsd_rho: 0.1 | |
| opsd_query_sigma: 0.278 | |
| opsd_n_ascent: 2 | |
| opsd_eta_tgt: 1.0 | |
| opsd_reward_kind: hpsv3_general | |
| opsd_target_chunk: 1 | |
| opsd_eps_grad: 1.0e-12 | |
| opsd_eps_gamma: 1.0e-05 | |
| opsd_dual_neg: true | |
| opsd_state_mode: forward | |
| opsd_sigma_mode: lognormal | |
| opsd_logit_mean: -2.053 | |
| opsd_logit_std: 0.6 | |
| opsd_r_mode: given_t | |
| refl_use_advantage: false | |
| opsd_dir_mode: grad | |
| reward_ckpt_path: '' | |
| grpo_noise_level: 0.7 | |
| solver: | |
| generator: | |
| lr: 3.0e-06 | |
| warmup_steps: 0 | |
| beta1: 0.9 | |
| beta2: 0.999 | |
| eps: 1.0e-08 | |
| weight_decay: 0.0001 | |
| max_grad_norm: 1.0 | |
| aux_v: | |
| lr: 1.0e-05 | |
| warmup_steps: 0 | |
| beta1: 0.9 | |
| beta2: 0.999 | |
| eps: 1.0e-08 | |
| weight_decay: 0.0 | |
| max_grad_norm: 1.0 | |
| train: | |
| total_steps: 0 | |
| save_interval: 50 | |
| log_interval: 1 | |
| seed: 42 | |
| batch_size: 2 | |
| gradient_accumulation_steps: 1 | |
| autocast_dtype: bf16 | |
| resume_from: '' | |
| use_ema: true | |
| ema_decay: 0.9 | |
| ema_every: 1 | |
| distributed: | |
| strategy: fsdp | |
| fsdp_sharding: hybrid | |
| ddp_find_unused_parameters: null | |
| logging: | |
| project: fewsteprl-wan21 | |
| run_name: meanflowopsd | |
| entity: '' | |
| tags: | |
| - wan2.1 | |
| - video | |
| - anyflow | |
| - meanflow-nft | |
| - 480p | |
| - 81f | |
| - rpd | |
| - opsd | |
| - differentiable-reward | |
| - x0-form | |
| enabled: true | |
| eval: | |
| enabled: true | |
| eval_interval: 10 | |
| eval_prompt_source: dataset | |
| eval_prompt_path: '' | |
| dataset: wan_dancegrpo | |
| dataset_path: dataset | |
| reward_fn: | |
| hpsv3_general: 1.0 | |
| hpsv3_percentile: 1.0 | |
| videoalign_mq: 1.0 | |
| videoalign_ta: 1.0 | |
| reward_dataset_map: {} | |
| reward_ckpt_path: '' | |
| eval_num_steps: 4 | |
| eval_guidance_scale: 1.0 | |
| eval_batch_size: 1 | |
| num_media_images: 4 | |
| eval_seed: 12345 | |
| vbench: | |
| enabled: false | |
| aug_info_json: dataset/vbench/VBench_aug_full_info.json | |
| full_info_json: dataset/vbench/VBench_full_info.json | |
| num_samples_per_prompt: 5 | |
| num_inference_steps: 4 | |
| guidance_scale: 1.0 | |
| cache_dir: models/vbench | |
| output_subdir: vbench | |
| eval_every_epochs: 0 | |
| prompt_path: dataset/wan_dancegrpo | |
| output_dir: ./outputs/meanflowopsd | |