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:
- 842754bd3135163e3319b55c6bef8950c5e5e7bd0ce60e2b7851472c4092b57e
- Size of remote file:
- 3.46 GB
- SHA256:
- e61adc56be42a0b6d57d0723368284b20f48a8bfc652f490bf3d5e1ea5153d93
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