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", torch_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:
- 27019be6ecfe4b6defe6bea1a16d2542e6e62e50f50427be674690e1e803c610
- Size of remote file:
- 3.91 GB
- SHA256:
- 81dc5915fc3c3b170684534ca11ed6c535ddea5658793a801fac53b8d5281065
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