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:
- 3e1b1c01701dc67be68ae465d87a136174574637ddfd66fdee40c292f8a07f5a
- Size of remote file:
- 2.61 GB
- SHA256:
- 9ae5a758382b160bc8ac7a7deba3d71b62cc6348b28ce05ba4fb7db2775c5cf4
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