Instructions to use luchaoqi/overplusplus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use luchaoqi/overplusplus with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("luchaoqi/overplusplus", 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
| license: apache-2.0 | |
| # Over++: Generative Video Compositing for Layer Interaction Effects | |
| [Paper](https://huggingface.co/papers/2512.19661) | [Project page](https://overplusplus.github.io/) | |
| ## Overview | |
| This Hugging Face repository contains the transformer weights for the model used in the CogVideo pipeline [here](https://github.com/aigc-apps/VideoX-Fun). | |
| You can load the transformer weights using the command below: | |
| ``` | |
| python inference/cogvideox_fun/predict_v2v.py \ | |
| --config.experiment.save_foreground=True \ | |
| --config.experiment.save_path="output_temp" \ | |
| --config.data.data_rootdir="examples" \ | |
| --config.experiment.run_seqs="boy-water,pexles_car_drift" \ | |
| --config.experiment.skip_if_exists=False \ | |
| --config.data.dilate_width=0 \ | |
| --config.video_model.guidance_scale=6 \ | |
| --config.video_model.transformer_path="PATH/TO/CHECKPOINTS/diffusion_pytorch_model.safetensors" | |
| ``` | |
| For more details, please refer to the GitHub repository [here](https://github.com/luchaoqi/overplusplus?tab=readme-ov-file#single-gpu-inference) |