Instructions to use nitrosocke/classic-anim-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/classic-anim-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nitrosocke/classic-anim-diffusion", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit History
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Add `clip_sample=False` to scheduler to make model compatible with DDIM. (#13)
- Add `clip_sample=False` to scheduler to make model compatible with DDIM. (dedfa7e555f7e98dca5e900a6c2a2dc66da9b6c0) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>50f65cf
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Add diffusers model (#8)
- add diffusers weights (ab155697c61e0b4c01045f9cceda03e1dbdc888c) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>1390152