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:
- 34137c7a571e1f446d0df942e44b41134b6afe9403172cbc5c6a64d39f3a8fb8
- Size of remote file:
- 3.46 GB
- SHA256:
- f8a4dfce6072e1d7af41b5a4aa989f2cb4fc112afee0e306ae3780e7bd3c412e
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