Instructions to use lora-library/https-huggingface-co-lora-library-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lora-library/https-huggingface-co-lora-library-test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lora-library/https-huggingface-co-lora-library-test") prompt = "Ping hair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- a04e35726782bd29664113ac06921baffcfaeea3ef66ceea0a04854b776a9c3a
- Size of remote file:
- 557 Bytes
- SHA256:
- 5dc9eacfeb00bd0bfeb98934a2309be01be65b288e0d747bbfc423b32679169f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.