Instructions to use hustvl/PixelHacker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hustvl/PixelHacker with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hustvl/PixelHacker", torch_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:
- ea6fdf1b331832c0554b8c4b9da2229f95e9bb1805dd92def3b9c3beeb8b135b
- Size of remote file:
- 3.45 GB
- SHA256:
- ceb615b88e3cc0d675e5516ab300bbe33457f0807af99b39671137a4af45b023
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