Instructions to use Bercraft/Anima-Base-v1.0-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Bercraft/Anima-Base-v1.0-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("Bercraft/Anima-Base-v1.0-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:
- b6bce415b7fe58dd5a634704d7c7a92b34a55591b7cc7d00c03de53b853a8651
- Size of remote file:
- 269 MB
- SHA256:
- fdcf606524892e35b270b96fc8bbd8d77e615ab882675a049f6e7c2ff6b71da3
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