Instructions to use nan2/clbenben with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nan2/clbenben with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nan2/clbenben", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 08d0bf98a71e5a464a615714cd719a734200715a1bf1a9e2702d77884ad274c1
- Size of remote file:
- 246 MB
- SHA256:
- 238c143b6e818157567d4170a958ba5405fbc741c968662c396df39c918feb67
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