Instructions to use xcpan/AnimateDiff-v3-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xcpan/AnimateDiff-v3-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xcpan/AnimateDiff-v3-diffusers", 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
- Xet hash:
- 386369034541c3db3076e5e2d6c586461d5e43ad070066aed8f9bca8e9fac639
- Size of remote file:
- 1.67 GB
- SHA256:
- d43181c61858b8a7abda1449b86486907b5ca3cf245f71c90735ca4b63e6c8c4
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