Instructions to use cuongdev/tonghop-v3-9000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/tonghop-v3-9000 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/tonghop-v3-9000", 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/tonghop-v3-9000: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/cuongdev/tonghop-v3-9000/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://cuongdev/tonghop-v3-9000/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/cuongdev/tonghop-v3-9000/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- 330302c158ada27da4d72d40dbc3a67eea50de6e5f6914ba72a66b8fc381c3e8
- Size of remote file:
- 3.46 GB
- SHA256:
- 7c0279b9ba8ee37f2bf4a2945d21c3d7181d90a1f61fe295f1ce5d336da3fe55
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