Instructions to use udg/delib with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use udg/delib with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("udg/delib", 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:
- 922dc4a46f2b216524c935aa9aeaf770ec5b07f7e9378ab53ad400a95ead69b8
- Size of remote file:
- 1.36 GB
- SHA256:
- f6d6c480bf8ea7d3c1b7de05f5045dffaac2859bf22bb58c62b64f3529727b65
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