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:
- 004299210328fbd0a714bff8b9e91ccb3f00172bb81f4fc867c32af845314905
- Size of remote file:
- 2.61 GB
- SHA256:
- 55ce9c9be165121131e152bb0bff65c9c622b16c7f22346e6f7ab6ffc4ad4363
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