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README.md

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+## AgentEvol-7B
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+<p align="center">
+  📃 <a href="TODO" target="_blank">Paper</a > • 🌐 <a href="https://agentgym.github.io/" target="_blank">Project Page</a > • 💻 <a href="https://github.com/WooooDyy/AgentGym" target="_blank">[Github Repo]</a> •   📚 <a href="https://huggingface.co/datasets/AgentGym/AgentTraj-L" target="_blank">[Trajectory Dataset]</a >  • 📈 <a href="https://huggingface.co/datasets/AgentGym/AgentEval" target="_blank">[Eval Benchmark]</a>  • 🤗 <a href="https://huggingface.co/AgentGym/AgentEvol-7B" target="_blank">Model (AgentEvol-7B)</a ><br>
+</p >
+
+**AgentEvol** is a novel method to evolve generall-capable LLM-based agents across multiple environments. AgentEvol first trains a base generally-capable agent with behavioral cloning, equipping it with basic abability and prior knowledgs. Subsequently, the agent is allowed to perform exploration and learning acorss various tasks and environments.
+
+**AgentEvol-7B** is trained with the AgentEvol algorithm on Llama-2-Chat-7B. The model is first trained on the AgentTraj set with behavioural cloning. Next it performs exploration and learning from a broader set of instructions. After evolution, its performance outperforms SOTA models on many tasks.
+
+## 🔖 Citation
+
+- TODO