Instructions to use lilpotat/urp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lilpotat/urp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lilpotat/urp", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c644fd8a3d6b39e6044716ffe231925e4bc5fbe15a01b8aad58ef1bf0a53620b
- Size of remote file:
- 492 MB
- SHA256:
- a1b9e9c05993ca58d360fe6f651a1f6342a9a9b6d044f6039d6557065ce1788c
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