Instructions to use jacklishufan/diffusion-kto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jacklishufan/diffusion-kto with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jacklishufan/diffusion-kto", 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:
- 2b0d483bca2a011e8f8a50c91c9311d2480d623e90ff7b98d7de910293fc4a4e
- Size of remote file:
- 250 MB
- SHA256:
- cfc08c7d25bbf860be207e2ce48a59c83668b02e1efacdc559014834b289c2ef
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