Instructions to use johannezz/DiffSensei with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use johannezz/DiffSensei with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("johannezz/DiffSensei", 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:
- b1fcd3ad221f6f00eea0fda209b11fa777b7a84af8683c6d29d65799da6a06e0
- Size of remote file:
- 343 MB
- SHA256:
- 8a5acf1f633a72d0a539dcded1b9b292ab1e9ec99d3100dddbd8e6b6b00a01b7
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