Instructions to use himmug/himanshu-sb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use himmug/himanshu-sb with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("himmug/himanshu-sb", 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 himmug/himanshu-sb: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/himmug/himanshu-sb/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://himmug/himanshu-sb/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/himmug/himanshu-sb/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- dad9af86a91768e98a43aefce8b0c7d750b88c9e7a21928a4125eae8ec6ad90e
- Size of remote file:
- 681 MB
- SHA256:
- 858aaa97ebd46e3d994b9f4c29fc29aee9e6abe1e9e5db55f0c46211cb79aa66
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.