Instructions to use recoilme/vae7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use recoilme/vae7 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("recoilme/vae7", 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:
- f2581572eb59b9b8a1604c7dfdf7ce4eba876efd117217bc589febdb4e0592e6
- Size of remote file:
- 383 MB
- SHA256:
- ad60166e5360ca9fd3e53e22a42ddd59a8b513f4a4dda5126d9b1c3ccd1431c8
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