Instructions to use cuongdev/tonghop-v5-4000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/tonghop-v5-4000 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-v5-4000", 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-v5-4000: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/cuongdev/tonghop-v5-4000/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://cuongdev/tonghop-v5-4000/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/cuongdev/tonghop-v5-4000/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- e8d2b87e739096a1a55ac91fa506eb717b310edec98b96cbe9093574d292ef61
- Size of remote file:
- 3.46 GB
- SHA256:
- 5dca60b51a4849f4663d60a3826e1a00d2ced512dd68ceb39e938e71d0b6e3b0
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