Instructions to use Alexwww/rejart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Alexwww/rejart with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Alexwww/rejart", 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 Alexwww/rejart: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/Alexwww/rejart/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Alexwww/rejart/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Alexwww/rejart/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 6e68ac4e21d19b0504d0fe5bdb09d7636f72f6b6b9bce169e9960e78ed41ca22
- Size of remote file:
- 246 MB
- SHA256:
- fb9782ecf28910226aad3acb4d61ab14438571b3fc287226e3f3a3898cd5bb47
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.