Instructions to use cuongdev/cothu2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/cothu2 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/cothu2", 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:
- 132dac4d487277c345887197699ab36a522dc2034faa994a3f20fe70ff24af59
- Size of remote file:
- 681 MB
- SHA256:
- 1a56deae28481cb0203190c6998f968cafeb1c86827b257e0ce0979a133b0ea0
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