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--- |
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license: mit |
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language: |
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- en |
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base_model: |
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- meta-llama/Llama-3.1-70B-Instruct |
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--- |
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# Llama-3.1-70B-Instruct + ToolQA (Finetuned) |
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This model is based on **Llama-3.1-70B-Instruct**, fine-tuned on the [ToolQA dataset](https://github.com/night-chen/ToolQA) for multi-step tool-use reasoning tasks. |
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## Training Details |
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* **Dataset**: [ToolQA](https://github.com/night-chen/ToolQA) – a benchmark designed for evaluating agents' tool-use capabilities in complex environments. |
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* **Training Framework**: [Memento-No-More](https://arxiv.org/abs/2502.01562) – a novel framework for teaching models to internalize hints and perform multi-skill reasoning. |
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* **Fine-tuning Rounds**: 3 |
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* **Model Base**: [Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct) |
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## Reference |
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For detailed information on the training methodology, architecture, and evaluations, please refer to our paper: |
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> **Alakuijala, M., Gao, Y., Ananov, G., Kaski, S., Marttinen, P., Ilin, A., & Valpola, H.** (2025). *Memento No More: Coaching AI Agents to Master Multiple Tasks via Hints Internalization*. arXiv preprint [arXiv:2502.01562](https://arxiv.org/abs/2502.01562). |
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