Instructions to use lavinal712/sd-control-lora-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lavinal712/sd-control-lora-segmentation 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("lavinal712/sd-control-lora-segmentation", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" 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
- Xet hash:
- c2c5e3462c7961c7a3c4e43e45c5464c8031fbdab17f636f8b982902e1a61472
- Size of remote file:
- 271 MB
- SHA256:
- 58b40f6f67c5e84dd446081301ee47d8ffb91f010678bbc9c5056254a53b8742
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