Instructions to use cuongdev/cothu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/cothu 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/cothu", 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:
- 7b8a489315f9c1d91a6dad66d89d6f0a92c1f73066babbf19aa28fa7fdf56636
- Size of remote file:
- 3.46 GB
- SHA256:
- 0fb5cf47b2210d6480cfe3667849159105fae9cd554081b99d31f83b90f12e09
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