Instructions to use cuongdev/tonghop-v2-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/tonghop-v2-1 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-v2-1", 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-v2-1: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/cuongdev/tonghop-v2-1/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://cuongdev/tonghop-v2-1/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/cuongdev/tonghop-v2-1/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- f1d6c3d194e9355f54872b6a75c01fef8cb5bcfa0a0856eebdd7f68e8918b892
- Size of remote file:
- 3.46 GB
- SHA256:
- be55d87a1ae4ba68fc00bfd4f66ad1d12c929ba0e3d00dd568bb33d667775f68
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