Instructions to use cuongdev/7nguoi-1500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/7nguoi-1500 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/7nguoi-1500", 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/7nguoi-1500: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/cuongdev/7nguoi-1500/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://cuongdev/7nguoi-1500/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/cuongdev/7nguoi-1500/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- dc0485e0dc882e59d2c84e094d57721c4247ff6e984eea8e8d01a859298ec02a
- Size of remote file:
- 3.46 GB
- SHA256:
- 52ab0776453d0e76e931f0237c40518bdc29d4b554e51022e4de956e02883306
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