Instructions to use lightx2v/Wan2.2-Distill-Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Wan2.2-Distill-Models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lightx2v/Wan2.2-Distill-Models", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use lightx2v/Wan2.2-Distill-Models 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
- Notebooks
- Google Colab
- Kaggle
add pipeline tag for better discoverability :)
#3
by linoyts HF Staff - opened
README.md
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license: apache-2.0
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tags:
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library_name: diffusers
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license: apache-2.0
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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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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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---
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