Instructions to use FudanCVL/EffectErase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FudanCVL/EffectErase with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FudanCVL/EffectErase", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Update model card with paper links and improved metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the community science team at Hugging Face.
This PR improves the model card for EffectErase by:
- Linking the repository to the official paper 2603.19224.
- Updating the metadata with specific tags for video object removal and inpainting to make the model easier to find.
- Refining the README to ensure all links (Project Page, GitHub, arXiv) point to the correct resources.
- Cleaning up the abstract for better readability.