Instructions to use chamuditha4/test22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chamuditha4/test22 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("chamuditha4/test22", 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:
- 007b2a14b8fda9433ae733764790894943d982f45a55583c14fc9cf613dee73a
- Size of remote file:
- 1.72 GB
- SHA256:
- aafe70e42d399738ac2c49e9447ee088c6b87fbc23e605452756c33ce9ffc0eb
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