Instructions to use nitrosocke/redshift-diffusion-768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/redshift-diffusion-768 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nitrosocke/redshift-diffusion-768", 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 nitrosocke/redshift-diffusion-768: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/nitrosocke/redshift-diffusion-768/resolve/refs%2Fpr%2F13/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://nitrosocke/redshift-diffusion-768@refs/pr/13/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/nitrosocke/redshift-diffusion-768/resolve/refs%2Fpr%2F13/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- de438cbffb9d86bb5489b0124e148143126821dbb7dd33a17c8c4209e0255b4e
- Size of remote file:
- 3.46 GB
- SHA256:
- 2c487b88e858e75aa4a8f4909b6932c593a049e3b55e850244377d289b0c7e34
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