Instructions to use ByteDance/AnimateDiff-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/AnimateDiff-Lightning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ByteDance/AnimateDiff-Lightning", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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by thanhnhanvta - opened
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- animatediff
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library_name: diffusers
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inference: false
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---
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# AnimateDiff-Lightning
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- animatediff
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library_name: diffusers
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inference: false
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datasets:
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- HuggingFaceM4/the_cauldron
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language:
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- vi
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metrics:
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- bertscore
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---
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# AnimateDiff-Lightning
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