Instructions to use Charles2023/cathead-sd1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Charles2023/cathead-sd1-5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Charles2023/cathead-sd1-5", 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 Charles2023/cathead-sd1-5: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/Charles2023/cathead-sd1-5/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Charles2023/cathead-sd1-5/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Charles2023/cathead-sd1-5/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 21f10bfda3318d9faf57434dca5ff0a5655950c092bfd80e4e929b498d154dcf
- Size of remote file:
- 246 MB
- SHA256:
- 248d1247eb946273ee3d831291d62d36ce2b83e91fa8d142244d851e855874e4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.