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---
license: apache-2.0
base_model:
- OpenGVLab/VideoChat2_stage3_Mistral_7B
---
<a href='https://arxiv.org/abs/2504.12083'><img src='https://img.shields.io/badge/arXiv-paper-red'></a>
<a href='https://pritamqu.github.io/RRPO/'><img src='https://img.shields.io/badge/project-RRPO-blue'></a>
<a href='https://huggingface.co/datasets/pritamqu/self-alignment'><img src='https://img.shields.io/badge/huggingface-datasets-green'></a>
<a href='https://huggingface.co/collections/pritamqu/rrpo-67fbc8c048b298a5fdfb167b'><img src='https://img.shields.io/badge/model-checkpoints-yellow'></a>
</a><a href='https://github.com/pritamqu/RRPO'><img src='https://img.shields.io/badge/github-repository-purple'></a>
## Installation
Clone the repository and navigate to the RRPO directory:
```sh
git clone https://github.com/pritamqu/RRPO
cd RRPO
conda create -n videochat2 python=3.10 -y
conda activate videochat2
pip install -r videochat2.txt
```
## Download weights
```
# base model
git clone [email protected]:OpenGVLab/VideoChat2_stage3_Mistral_7B
# RRPO weights
git clone [email protected]:pritamqu/VideoChat2_stage3_Mistral_7B-RRPO-16f-LORA
```
## Inference
```
conda activate videochat2
BASE_WEIGHTS="./VideoChat2_stage3_Mistral_7B"
WEIGHTS_ROOT="./"
python inference.py \
--base_model_name "videochat2_mistral_7b" \
--model-path ${BASE_WEIGHTS} \
--model-path2 ${WEIGHTS_ROOT}"/VideoChat2_stage3_Mistral_7B-RRPO-16f-LORA" \
--video_path "sample_video.mp4" \
--question "Describe this video." \
--model_max_length 1024
``` |