Update README.md

README.md

@@ -5,10 +5,20 @@ datasets:
 base_model:
 - google/gemma-2-27b
 ---
+---
+license: mit
+datasets:
+- openai/summarize_from_feedback
+base_model:
+- google/gemma-2-27b
+---
 # Model Card for MA-RLHF
 <a href="https://iclr.cc/Conferences/2024" target="_blank">
       <img alt="ICLR 2025" src="https://img.shields.io/badge/Proceedings-ICLR2025-red" />
 </a>
+<a href="https://github.com/ernie-research/MA-RLHF" target="_blank">
+      <img alt="Github" src="https://img.shields.io/badge/Github-MA_RLHF-green" />
+   </a>
 
 This repository contains the official checkpoint for [Reinforcement Learning From Human Feedback with Macro Actions (MA-RLHF)](https://arxiv.org/pdf/2410.02743). 
 
@@ -16,6 +26,18 @@ This repository contains the official checkpoint for [Reinforcement Learning Fro
 
 MA-RLHF is a novel framework that integrates macro actions into conventional RLHF. The macro actions are sequences of tokens or higher-level language constructs, with can be computed through different defined termination conditions, like n-gram based, perplexity-based, or parsing-based termination conditions. By introducing macro actions into RLHF, we reduce the number of decision points and shorten decision trajectories, alleviating the credit assignment problem caused by long temporal distances.
 
+
+|Model|Checkpoint|Base Model|Dataset| 
+|-----|----------|-|-|
+|TLDR-Gemma-2B-MA-PPO-Fixed5|🤗 [HF Link](https://huggingface.co/baidu/TLDR-Gemma-2B-MA-PPO-Fixed5)|[google/gemma-2b](https://huggingface.co/google/gemma-2b)|[openai/summarize_from_feedback](https://huggingface.co/datasets/openai/summarize_from_feedback)
+|TLDR-Gemma-7B-MA-PPO-Fixed5|🤗 [HF Link](https://huggingface.co/baidu/TLDR-Gemma-7B-MA-PPO-Fixed5)|[google/gemma-7b](https://huggingface.co/google/gemma-7b)|[openai/summarize_from_feedback](https://huggingface.co/datasets/openai/summarize_from_feedback)
+|TLDR-Gemma-2-27B-MA-PPO-Fixed5|🤗 [HF Link](https://huggingface.co/baidu/TLDR-Gemma-2-27B-MA-PPO-Fixed5)|[google/gemma-2-27b](https://huggingface.co/google/gemma-2-27b)|[openai/summarize_from_feedback](https://huggingface.co/datasets/openai/summarize_from_feedback)
+|HH-RLHF-Gemma-2B-MA-PPO-Fixed5|🤗 [HF Link](https://huggingface.co/baidu/HH-RLHF-Gemma-2B-MA-PPO-Fixed5) |[google/gemma-2b](https://huggingface.co/google/gemma-2b)|[Dahoas/full-hh-rlhf](https://huggingface.co/datasets/Dahoas/full-hh-rlhf)
+|HH-RLHF-Gemma-7B-MA-PPO-Fixed5|🤗 [HF Link](https://huggingface.co/baidu/HH-RLHF-Gemma-7B-MA-PPO-Fixed5) |[google/gemma-7b](https://huggingface.co/google/gemma-7b)|[Dahoas/full-hh-rlhf](https://huggingface.co/datasets/Dahoas/full-hh-rlhf)
+|APPS-Gemma-2B-MA-PPO-Fixed10|🤗 [HF Link](https://huggingface.co/baidu/APPS-Gemma-2B-MA-PPO-Fixed10) |[google/codegemma-2b](https://huggingface.co/google/codegemma-2b)|[codeparrot/apps](https://huggingface.co/datasets/codeparrot/apps)
+|APPS-Gemma-7B-MA-PPO-Fixed10|🤗 [HF Link](https://huggingface.co/baidu/APPS-Gemma-7B-MA-PPO-Fixed10) |[google/codegemma-7b-it](https://huggingface.co/google/codegemma-7b-it)|[codeparrot/apps](https://huggingface.co/datasets/codeparrot/apps)
+
+
 ## Model Usage
 
 ```python