Instructions to use lora-library/lora-ruchelle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lora-library/lora-ruchelle with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lora-library/lora-ruchelle") prompt = "fr" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 2c59816d3dbeb981d45e32a56a241ccf4caf4cd8f0604c824329295ad0f10188
- Size of remote file:
- 4 MB
- SHA256:
- 3956c854e7e6c4828b325b9ed1a9673ec01ff205318eb14dc86f1f85ec041a3b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.