Instructions to use cuongdev/3nguoi-2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/3nguoi-2000 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/3nguoi-2000", 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:
- b145d940e09d7382e877d0317bb4f8808e099e4b847bc9bd91755e13352960e4
- Size of remote file:
- 3.46 GB
- SHA256:
- 147efdca8ef36d42102f9dbc664a13a59aa4a79f8fcaf278eae5d61bfbfefcc1
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