Instructions to use lightx2v/Wan2.2-Distill-Loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Wan2.2-Distill-Loras 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("Wan-AI/Wan2.2-I2V-A14B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lightx2v/Wan2.2-Distill-Loras") prompt = "A man with short gray hair plays a red electric guitar." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") image = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Diffusion Single File
How to use lightx2v/Wan2.2-Distill-Loras with Diffusion Single File:
# 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
- Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
add pipeline tag for better discoverability :) (#8)
Browse files- add pipeline tag for better discoverability :) (457a782aa7c6ad1c414399db0e390e6e44a41e73)
Co-authored-by: Linoy Tsaban <linoyts@users.noreply.huggingface.co>
README.md
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license: apache-2.0
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tags:
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base_model:
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library_name: diffusers
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# 🎬 Wan2.2 Distilled LoRA Models
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license: apache-2.0
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tags:
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- diffusion-single-file
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- comfyui
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- distillation
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- LoRA
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- video
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- video genration
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pipeline_tags:
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- image-to-video
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- text-to-video
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base_model:
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- Wan-AI/Wan2.2-I2V-A14B
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library_name: diffusers
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pipeline_tag: image-to-video
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# 🎬 Wan2.2 Distilled LoRA Models
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