Update README.md

README.md

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 This reward model achieves a score of 88.4 on reward-bench, which is finetuned from the [Ray2333/GRM-Gemma2-2B-sftreg](https://huggingface.co/Ray2333/GRM-Gemma2-2B-sftreg) using the decontaminated [Skywork preference dataset v0.2](https://huggingface.co/datasets/Skywork/Skywork-Reward-Preference-80K-v0.2). 
 We obtain a **SOTA 2B reward model** that can outperform a series of 8B reward models and even surpass gpt4/gemini as a judge.
 
-Check our GRM series at 🤗[hugging face](https://huggingface.co/collections/Ray2333/grm-66882bdf7152951779506c7b) and our paper at [Arxiv](https://arxiv.org/abs/2406.10216).
+Check our GRM series at 🤗[hugging face](https://huggingface.co/collections/Ray2333/grm-66882bdf7152951779506c7b), our paper at [Arxiv](https://arxiv.org/abs/2406.10216), and github repo at [Github](https://github.com/YangRui2015/Generalizable-Reward-Model).