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
LoRA DreamBooth - lora-ruchelle
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on the instance prompt "fr" using DreamBooth. You can find some example images in the following.
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Model tree for lora-library/lora-ruchelle
Base model
runwayml/stable-diffusion-v1-5


