Instructions to use buxiangzhiren/GeoRemover with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use buxiangzhiren/GeoRemover 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("buxiangzhiren/GeoRemover", 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
Add `library_name` and GitHub link
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Adding the
library_name: diffuserstag to the metadata. This enables the automated "how to use" widget on the model page, as the implementation is built on a Diffusion model (FLUX.1-Fill-dev) with LoRA adapters. - Including a direct link to the GitHub repository in the model card content for easier access to the code.
The existing arXiv paper link has been retained as per guidelines.
buxiangzhiren changed pull request status to merged