File size: 2,144 Bytes
44342d1 57035af 44342d1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 |
---
license: apache-2.0
datasets:
- yzy666/SVBench
language:
- en
metrics:
- code_eval
base_model:
- OpenGVLab/InternVideo2_5_Chat_8B
pipeline_tag: visual-question-answering
---
# Model Card for StreamingChat
<!-- Provide a quick summary of what the model is/does. -->
This dataset card aims to provide a comprehensive overview of the StreamingChat model. For details, see our [Project](https://yzy-bupt.github.io/SVBench/), [Paper](https://arxiv.org/abs/2502.10810), [Dataset](https://huggingface.co/datasets/yzy666/SVBench) and [GitHub repository](https://github.com/yzy-bupt/SVBench).
## **Dataset Description**
**StreamingChat** is a streaming video understanding model built upon [InternVideo2.5](https://huggingface.co/OpenGVLab/InternVideo2_5_Chat_8B). It utilizes Streaming video dialogue data, including temporal dialogue paths from the [SVBench](https://huggingface.co/datasets/yzy666/SVBench) training set. The model is fine-tuned using a static resolution strategy, enabling it to process several minutes of video at a rate of 1 FPS. Images are interleaved with language tokens, with each image comprising 16 tokens. This model aims to catalyze progress in streaming video understanding.
## **Uses**
Download the StreamingChat model from Hugging Face:
```bash
git clone https://huggingface.co/yzy666/StreamingChat_8B
```
Install Python dependencies:
```bash
conda create -n StreamingChat -y python=3.9.21
conda activate StreamingChat
conda install -y -c pytorch pytorch=2.5.1 torchvision=0.10.1
pip install transformers=4.37.2 opencv-python=4.11.0.84 imageio=2.37.0 decord=0.6.0
pip install flash-attn --no-build-isolation
```
Run the inference script directly：
```bash
python demo.py
```
## **Citation**
If you find our data useful, please consider citing our work!
```
@article{yang2025svbench,
title={SVBench: A Benchmark with Temporal Multi-Turn Dialogues for Streaming Video Understanding},
author={Yang, Zhenyu and Hu, Yuhang and Du, Zemin and Xue, Dizhan and Qian, Shengsheng and Wu, Jiahong and Yang, Fan and Dong, Weiming and Xu, Changsheng},
journal={arXiv preprint arXiv:2502.10810},
year={2025}
}
``` |