Instructions to use cuongdev/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/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/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:
- 42dc0c27bb8efd2461624001fa9890f4af7b9cefaec13f2e8f08f270eb2927d2
- Size of remote file:
- 3.46 GB
- SHA256:
- e68ee055b252f75085c087d9c65094c5d74cd2c6cd52b04c525e32576a50da71
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