Instructions to use cxyz/kjrg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cxyz/kjrg with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cxyz/kjrg", 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 cxyz/kjrg: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/cxyz/kjrg/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://cxyz/kjrg/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cxyz/kjrg/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 70b6cc821d7abbf962710f66fbfc13177ff2244c2215f7651e9e9f1c48c2a4b4
- Size of remote file:
- 246 MB
- SHA256:
- 17089dd36680aebc093799a1cead31c64a977d38005e903fb4988b54f35c15e7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.