Update README.md

README.md

@@ -10,17 +10,18 @@ library_name: transformers
 pipeline_tag: video-text-to-text
 ---
 
-[📃Paper](https://arxiv.org/abs/2406.15252) | [🌐Website](https://tiger-ai-lab.github.io/VideoScore/) | [💻Github](https://github.com/TIGER-AI-Lab/VideoScore) | [🛢️Datasets](https://huggingface.co/datasets/TIGER-Lab/VideoFeedback) | [🤗Model (VideoScore)](https://huggingface.co/TIGER-Lab/VideoScore) | [🤗Model (VideoScore-anno-only)](https://huggingface.co/TIGER-Lab/VideoScore-anno-only) | [🤗Model (VideoScore-v1.1)](https://huggingface.co/TIGER-Lab/VideoScore-v1.1)| [🤗Demo](https://huggingface.co/spaces/TIGER-Lab/VideoScore)
+[📃Paper](https://arxiv.org/abs/2406.15252) | [🌐Website](https://tiger-ai-lab.github.io/VideoScore/) | [💻Github](https://github.com/TIGER-AI-Lab/VideoScore) | [🛢️Datasets](https://huggingface.co/datasets/TIGER-Lab/VideoFeedback) | [🤗Model (VideoScore)](https://huggingface.co/TIGER-Lab/VideoScore) | [🤗Demo](https://huggingface.co/spaces/TIGER-Lab/VideoScore)
 
 
 ![VideoScore](https://tiger-ai-lab.github.io/VideoScore/static/images/teaser.png)
 
 ## Introduction
-- 🤯🤯Try on the new version [VideoScore-v1.1](https://huggingface.co/TIGER-Lab/VideoScore-v1.1), a variant from [VideoScore](https://huggingface.co/TIGER-Lab/VideoScore) with better performance in **"text-to-video alignment"** subscore and the support for **48 frames** in inference now!
+- 🤯🤯Try on the new version [VideoScore-v1.1](https://huggingface.co/TIGER-Lab/VideoScore-v1.1), a variant from [VideoScore](https://huggingface.co/TIGER-Lab/VideoScore) with better performance in **"text-to-video alignment"** subscore and the support for **48 frames** in inference now! It takes [Mantis-8B-Idefics2](https://huggingface.co/TIGER-Lab/Mantis-8B-Idefics2) as base model,
+and is trained on trained on [VideoFeedback](https://huggingface.co/datasets/TIGER-Lab/VideoFeedback) dataset.
 
-- [VideoScore](https://huggingface.co/TIGER-Lab/VideoScore) series is a video quality evaluation model series, taking [Mantis-8B-Idefics2](https://huggingface.co/TIGER-Lab/Mantis-8B-Idefics2) as base-model
+- [VideoScore](https://huggingface.co/TIGER-Lab/VideoScore) series is a video quality evaluation model series, taking [Mantis-8B-Idefics2](https://huggingface.co/TIGER-Lab/Mantis-8B-Idefics2) or [Qwen/Qwen2-VL](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct) as base-model
 and trained on [VideoFeedback](https://huggingface.co/datasets/TIGER-Lab/VideoFeedback),
-a large video evaluation dataset with multi-aspect human scores. 
+a large video evaluation dataset with multi-aspect human scores.
 
 - Following VideoScore, VideoScore-v1.1 can also reach about 75 Spearman correlation with humans on VideoFeedback-test, surpassing all the MLLM-prompting methods and feature-based metrics. 
 VideoScore-v1.1 also beat the best baselines on other two benchmarks GenAI-Bench and VBench, showing high alignment with human evaluations.