Instructions to use falca/rev_animated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use falca/rev_animated with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("falca/rev_animated", 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
- Xet hash:
- bd33046e634bd56d7ff4cb034482da963f714bec46ea68a06caf58bb415a4e53
- Size of remote file:
- 3.44 GB
- SHA256:
- fdcda72cd0e454ef53f9a796cbcddfddf70527c7b0afa6d678de455a69ffe2d9
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