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 text_encoder/pytorch_model.bin from nitrosocke/redshift-diffusion-768: direct link, hf CLI and curl.
- Browser
- Download file 1.36 GB
-
https://huggingface.co/nitrosocke/redshift-diffusion-768/resolve/0b6609f8bf1b1a1703829a47381794de4dbf7138/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://nitrosocke/redshift-diffusion-768@0b6609f8bf1b1a1703829a47381794de4dbf7138/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nitrosocke/redshift-diffusion-768/resolve/0b6609f8bf1b1a1703829a47381794de4dbf7138/text_encoder/pytorch_model.bin
1.36 GB
- Xet hash:
- fe03d4833db151b1ec5641a8b3bcc8478293bfe0fd9746892163f743c5fe5cfe
- Size of remote file:
- 1.36 GB
- SHA256:
- c183e0abb36176116fe96ecd7d0ff86211ccee934c70528e8f0fb51fbd98740a
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