Instructions to use cuongdev/tvchau-1500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/tvchau-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/tvchau-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/tvchau-1500: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/cuongdev/tvchau-1500/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://cuongdev/tvchau-1500/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/cuongdev/tvchau-1500/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- 8ee730c2f67ad00adee971b9d1800d7997672a42f06d099149184be95c039c38
- Size of remote file:
- 3.46 GB
- SHA256:
- a1597f11e635c2f7a569b3655c01f652f30b679e1d92b01f2e3917897fab8deb
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