Instructions to use ChuuniZ/xcw-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ChuuniZ/xcw-models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ChuuniZ/xcw-models", 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:
- 99274b0755e9c542f42aa9102a2fe43346c45db38c7fe7f1f01f5acd525c5f09
- Size of remote file:
- 849 MB
- SHA256:
- 367a738b27e0556e703991e8160fe6b5217bec6c158a72a890d131dd11ba74f6
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