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", 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:
- 18ef93abc57dcf35a4d8cc16218e7f14b175d4ca1c679a1c45cbe41c29e21ccc
- Size of remote file:
- 3.45 GB
- SHA256:
- ef5e28199cd03344ac22a6e6ff456ba8b868e83fb90d8174cc2ad83d7ef4296c
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