README.md

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license: mit
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# Echo: A Large Language Model with Temporal Episodic Memory

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  <img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" width="120" alt="HuggingFace Logo"/>
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<p align="center">
  <a href="https://github.com/1920993165/echo">🛠️ <b>Code</b></a> &nbsp; | &nbsp;
  <a href="https://huggingface.co/datasets/ALmonster/Echo-v1">📚 <b>Dataset</b></a> &nbsp; | &nbsp;
  <a href="https://huggingface.co/ALmonster/Echo1-7B">🧠 <b>7B Model</b></a> &nbsp; | &nbsp;
  <a href="https://huggingface.co/ALmonster/Echo1-72B">🧠 <b>72B Model</b></a>
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## 🚀 Welcome to Echo!

**Echo** is a cutting-edge large language model (LLM) designed with temporal episodic memory, enabling advanced reasoning and context retention. We invite the community to explore, use, and cite our work!

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## 📖 Citation

If you use Echo in your research or applications, please cite us:

```bibtex
@misc{liu2025echolargelanguagemodel,
  title={Echo: A Large Language Model with Temporal Episodic Memory},
  author={WenTao Liu and Ruohua Zhang and Aimin Zhou and Feng Gao and JiaLi Liu},
  year={2025},
  eprint={2502.16090},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2502.16090},
}
```

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## 🌟 Get Involved

We welcome contributions, feedback, and collaboration from the community. Feel free to open issues or pull requests on our [GitHub](https://github.com/1920993165/echo)!

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<p align="center">
  <b>Empowering AI with memory. Echo: Remember, Reason, Respond.</b>
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