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
metadata
license: apache-2.0
Over++: Generative Video Compositing for Layer Interaction Effects
Overview
This Hugging Face repository contains the transformer weights for the model used in the CogVideo pipeline here.
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