Image-to-Video
Diffusers
Safetensors
Wan2.2
English
Chinese
WanPipeline
video-generation
visual-reasoning
reinforcement-learning
rlvr
vbvr-pro
Instructions to use Video-Reason/VBVR-Pro-Wan2.2-TI2V-5B-RLVR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Video-Reason/VBVR-Pro-Wan2.2-TI2V-5B-RLVR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Video-Reason/VBVR-Pro-Wan2.2-TI2V-5B-RLVR", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Wan2.2
How to use Video-Reason/VBVR-Pro-Wan2.2-TI2V-5B-RLVR 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
| { | |
| "_class_name": "WanPipeline", | |
| "_diffusers_version": "0.37.1", | |
| "_name_or_path": "Wan-AI/Wan2.2-TI2V-5B-Diffusers", | |
| "boundary_ratio": null, | |
| "expand_timesteps": true, | |
| "scheduler": [ | |
| "diffusers", | |
| "UniPCMultistepScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "UMT5EncoderModel" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "T5Tokenizer" | |
| ], | |
| "transformer": [ | |
| "diffusers", | |
| "WanTransformer3DModel" | |
| ], | |
| "transformer_2": [ | |
| null, | |
| null | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKLWan" | |
| ] | |
| } | |