Instructions to use huemin/fxhash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use huemin/fxhash with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("huemin/fxhash", 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 huemin/fxhash: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/huemin/fxhash/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://huemin/fxhash@refs/pr/1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/huemin/fxhash/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- a61dd6ab57c797b1624abfdb3ded24f8a80eda2b0c0a853ce9825170f4c388cd
- Size of remote file:
- 246 MB
- SHA256:
- 9ab754067ad03cb25a851efd84d6843756b5182df2da870d73e3173d190114ef
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