Instructions to use Hugol33/epgaxpp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Hugol33/epgaxpp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Hugol33/epgaxpp", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 908f7d33cc3bf7475156ce82f9a503efac8969c0829b4b636bc0c6234b5e5dba
- Size of remote file:
- 167 MB
- SHA256:
- c083a5be369492812f4f97c0a1ee61852a415bd8079368c456e3501744017ed7
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