Image-to-Image
Diffusers
StableDiffusionXLControlNetInpaintPipeline
stable-diffusion-xl
lora
template:sd-lora
inpainting
light-estimation
relighting
Instructions to use DiffusionLight/TurboLoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DiffusionLight/TurboLoRA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("DiffusionLight/TurboLoRA") prompt = "a perfect mirrored reflective chrome ball sphere, a perfect black dark mirrored reflective chrome ball sphere" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Upload pytorch_lora_weights.safetensors
Browse files
pytorch_lora_weights.safetensors
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