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:
- fdc9d7663e7d825736cb72a004b38b7af46d538fbb564d4540da220df3a3232d
- Size of remote file:
- 3.45 GB
- SHA256:
- a13cc4f7aa55c3ae98d414a42aa3e17df95a0cd21bdbf6511bc0aae051de7a16
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