Instructions to use cuongdev/chung-thu3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/chung-thu3 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/chung-thu3", 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
Download unet/diffusion_pytorch_model.bin from cuongdev/chung-thu3: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/cuongdev/chung-thu3/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://cuongdev/chung-thu3/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/cuongdev/chung-thu3/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- 77f4ba6029b0a29b68bb94604744f58a75f5d768e374e62a5ddd47b08e48393d
- Size of remote file:
- 3.46 GB
- SHA256:
- 74c035ec7ff797338f1c1e1980c27e23bdf1e6209cedc0204f3ca0244542a685
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