Instructions to use cuongdev/cuong-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/cuong-test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cuongdev/cuong-test", 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:
- 634d20331684022a98d2a22b67e239b9bb83fd0893ed711abd8df85b7277e590
- Size of remote file:
- 681 MB
- SHA256:
- 42ecabef3fe8745f4e60ec0ee32924b867892f25559af92fb7e1b1b3ed99f4ed
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