Instructions to use flax/StudioGhibli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use flax/StudioGhibli with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("flax/StudioGhibli", 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
- Draw Things
- DiffusionBee
- Xet hash:
- b7fb77b20968e81c8157bce9f3da181a5d5cd314ec67b1f87e89f24769d7a285
- Size of remote file:
- 3.44 GB
- SHA256:
- 8783d652c6b71791ee6f0e44a5b42e041d19c21ba5d2442faa076b28a8864768
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