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--- |
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license: apache-2.0 |
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datasets: |
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- togethercomputer/RedPajama-Data-1T |
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language: |
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- en |
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base_model: |
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- KoboldAI/fairseq-dense-125M |
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--- |
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# Data Scorer |
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The model to score data for data selection in the paper [Data Selection via Optimal Learning for Language Models](https://arxiv.org/abs/2410.07064). To use the model, follow the instructions [here](https://github.com/microsoft/LMOps/tree/main/data_selection#5-use-the-data-scorer-to-score-examples). |
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NOTE: you may need to download the [fairseq-125M](https://huggingface.co./KoboldAI/fairseq-dense-125M) to `${PATH_TO_DATA_SELECTION_REPO}/checkpoints/fairseq/125M` to prepare the tokenizer and config.json for the base model. |
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### Citation |
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```bibtex |
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@article{gu2024data, |
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title={Data Selection via Optimal Control for Language Models}, |
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author={Gu, Yuxian and Dong, Li and Wang, Hongning and Hao, Yaru and Dong, Qingxiu and Wei, Furu and Huang, Minlie}, |
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journal={arXiv preprint arXiv:2410.07064}, |
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year={2024} |
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} |
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``` |