Instructions to use cuongdev/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/test2 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/test2", 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:
- ac6856611642caaae564503c5be52c4b295c62c35981f50d3e3b706882818da1
- Size of remote file:
- 2.61 GB
- SHA256:
- c651a4c74ba1d00aa706259d953d8360364b3fc16f9db059ebff680e7b659054
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