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--- |
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license: apache-2.0 |
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datasets: |
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- ai2lumos/lumos_maths_ground_iterative |
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language: |
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- en |
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tags: |
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- language-agent |
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- maths |
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- reasoning |
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- grounding |
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--- |
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# πͺ Agent Lumos: Unified and Modular Training for Open-Source Language Agents |
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<p align="center"> |
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π<a href="https://allenai.github.io/lumos">[Website]</a> |
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π<a href="https://arxiv.org/abs/2311.05657">[Paper]</a> |
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π€<a href="https://huggingface.co/datasets?sort=trending&search=ai2lumos">[Data]</a> |
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π€<a href="https://huggingface.co/models?sort=trending&search=ai2lumos">[Model]</a> |
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π€<a href="https://huggingface.co/spaces/ai2lumos/lumos_data_demo">[Demo]</a> |
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</p> |
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We introduce πͺ**Lumos**, Language Agents with **Unified** Formats, **Modular** Design, and **Open-Source** LLMs. **Lumos** unifies a suite of complex interactive tasks and achieves competitive performance with GPT-4/3.5-based and larger open-source agents. |
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**Lumos** has following features: |
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* 𧩠**Modular Architecture**: |
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- 𧩠**Lumos** consists of planning, grounding, and execution modules built based on LLAMA-2-7B/13B and off-the-shelf APIs. |
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- π€ **Lumos** utilizes a unified data format that encompasses multiple task types, thereby enabling the developed agent framework to conveniently support a range of interactive tasks. |
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* π **Diverse Training Data**: |
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- π **Lumos** is trained with ~56K diverse high-quality subgoal/action annotations from ground-truth reasoning steps in existing benchmarks with GPT-4. |
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- βοΈ **Lumos** data can be instrumental for future research in developing open-source agents for complex interactive tasks. |
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* π **Competitive Performance**: |
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- π **Lumos** is comparable or even beats **GPT-series** agents on web/complex QA tasks Mind2Web and HotpotQA, and **larger open agents** on math and multimodal tasks. |
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- π **Lumos** exceeds contemporaneous agents that have been **fine-tuned** with in-domain HotpotQA, Mind2Web and ScienceQA annotations, such as **FiReAct**, **AgentLM**, and **AutoAct**. |
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- π **Lumos** performs better than open agent baseline formulations including **chain-of-thoughts** and **integrated** training. |
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- π **Lumos** surpasses larger open LLM agents and domain-specific agents on unseen tasks, WebShop and InterCode_SQL. |
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## Model Overview |
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`lumos_maths_ground_iterative` is a **grounding** module checkpoint finetuned on **maths** task in **Lumos-Iterative (Lumos-I)** formulation. |
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The training annotation is shown below: |
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| Training Data | Number | |
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|---|---| |
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|[`lumos_maths_ground_iterative`](https://huggingface.co/datasets/ai2lumos/lumos_maths_ground_iterative)|19778| |
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## Citation |
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If you find this work is relevant with your research, please feel free to cite our work! |
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``` |
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@article{yin2023lumos, |
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title={Agent Lumos: Unified and Modular Training for Open-Source Language Agents}, |
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author={Yin, Da and Brahman, Faeze and Ravichander, Abhilasha and Chandu, Khyathi and Chang, Kai-Wei and Choi, Yejin and Lin, Bill Yuchen}, |
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journal={arXiv preprint arXiv:2311.05657}, |
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year={2023} |
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} |
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``` |