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README.md

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-#以下为文本生成的 "tasks"示例，您可以从此网页中了解更多相关信息：https://modelscope.cn/docs/%E4%BB%BB%E5%8A%A1%E7%9A%84%E4%BB%8B%E7%BB%8D
-#tasks:
-#- text-generation
-license: Apache License 2.0
+datasets: 
+- THUDM/AgentInstruct
 ---
-###### 该模型当前使用的是默认介绍模版，处于“预发布”阶段，页面仅限所有者可见。
-###### 请根据[模型贡献文档说明](https://www.modelscope.cn/docs/%E5%A6%82%E4%BD%95%E6%92%B0%E5%86%99%E5%A5%BD%E7%94%A8%E7%9A%84%E6%A8%A1%E5%9E%8B%E5%8D%A1%E7%89%87)，及时完善模型卡片内容。ModelScope平台将在模型卡片完善后展示。谢谢您的理解。
-#### Clone with HTTP
-```bash
- git clone https://www.modelscope.cn/ZhipuAI/agentlm-13b.git
-```
+
+## AgentLM-13B
+
+<p align="center">
+  🤗 <a href="https://huggingface.co/datasets/THUDM/AgentInstruct" target="_blank">[Dataset] </a> • 💻 <a href="https://github.com/THUDM/AgentTuning" target="_blank">[Github Repo]</a> • 📌 <a href="https://THUDM.github.io/AgentTuning/" target="_blank">[Project Page]</a> • 📃 <a href="https://arxiv.org/abs/2310.12823" target="_blank">[Paper]</a> 
+</p>
+
+**AgentTuning** represents the very first attempt to instruction-tune LLMs using interaction trajectories across multiple agent tasks. Evaluation results indicate that AgentTuning enables the agent capabilities of LLMs with robust generalization on unseen agent tasks while remaining good on general language abilities. We have open-sourced the AgentInstruct dataset and AgentLM.
+
+## Models
+
+**AgentLM** models are produced by mixed training on AgentInstruct dataset and ShareGPT dataset from Llama-2-chat models. 
+
+The models follow the conversation format of [Llama-2-chat](https://huggingface.co/blog/llama2#how-to-prompt-llama-2), with system prompt fixed as 
+
+```
+You are a helpful, respectful and honest assistant.
+```
+
+7B, 13B, and 70B models are available on Huggingface model hub.
+
+|Model|Huggingface Repo|
+|---|---|
+|AgentLM-7B| [🤗Huggingface Repo](https://huggingface.co/THUDM/agentlm-7b) |
+|AgentLM-13B| [🤗Huggingface Repo](https://huggingface.co/THUDM/agentlm-13b) |
+|AgentLM-70B| [🤗Huggingface Repo](https://huggingface.co/THUDM/agentlm-70b) |
+
+## Citation
+
+If you find our work useful, please consider citing AgentTuning:
+
+```
+@misc{zeng2023agenttuning,
+      title={AgentTuning: Enabling Generalized Agent Abilities for LLMs}, 
+      author={Aohan Zeng and Mingdao Liu and Rui Lu and Bowen Wang and Xiao Liu and Yuxiao Dong and Jie Tang},
+      year={2023},
+      eprint={2310.12823},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```