Instructions to use cuongdev/5nguoi-5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/5nguoi-5000 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/5nguoi-5000", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 8517d3f753f88a751432ee32cbcc26b4e6f52547a668acb00a24e362feba6c3a
- Size of remote file:
- 335 MB
- SHA256:
- eac6df9beeebd0106fa4600ef1d15454ce83cb7853870ab3dd45ec89542838ab
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