Instructions to use MnLgt/erase_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MnLgt/erase_lora 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-inpainting", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("MnLgt/erase_lora") prompt = "erase" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
LoRA DreamBooth - jordandavis/erase_lora
These are LoRA adaption weights for runwayml/stable-diffusion-inpainting. The weights were trained on erase using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: True.
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