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This model repository presents "TinyPubMedBERT", a distillated [PubMedBERT (Gu et al., 2021)](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract) model. |
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The model is composed of 4-layers and distillated following methods introduced in the [TinyBERT paper](https://aclanthology.org/2020.findings-emnlp.372/) (Jiao et al., 2020). |
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* For the framework, please visit https://github.com/AstraZeneca/KAZU |
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* For the demo, please visit http://kazu.korea.ac.kr |
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* For details about the model, please see our paper entitled **Biomedical NER for the Enterprise with Distillated BERN2 and the Kazu Framework**, (EMNLP 2022 industry track). |
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TinyPubMedBERT is used as the initial weights for the training of the [dmis-lab/KAZU-NER-module-distil-v1.0](https://huggingface.co/dmis-lab/KAZU-NER-module-distil-v1.0) for the KAZU (Korea University and AstraZeneca) framework. |
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### Citation info |
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Joint-first authorship of **Richard Jackson** (AstraZeneca) and **WonJin Yoon** (Korea University). |
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<br>Please cite the paper using the simplified citation format provided in the following section, or find the [full citation information here](https://aclanthology.org/2022.emnlp-industry.63.bib) |
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``` |
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@inproceedings{YoonAndJackson2022BiomedicalNER, |
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title="Biomedical {NER} for the Enterprise with Distillated {BERN}2 and the Kazu Framework", |
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author="Yoon, Wonjin and Jackson, Richard and Ford, Elliot and Poroshin, Vladimir and Kang, Jaewoo", |
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booktitle="Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track", |
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month = dec, |
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year = "2022", |
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address = "Abu Dhabi, UAE", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2022.emnlp-industry.63", |
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pages = "619--626", |
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} |
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``` |
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This model used resources from [PubMedBERT paper](https://dl.acm.org/doi/10.1145/3458754) and [TinyBERT paper](https://aclanthology.org/2020.findings-emnlp.372/). |
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``` |
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Gu, Yu, et al. "Domain-specific language model pretraining for biomedical natural language processing." |
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ACM Transactions on Computing for Healthcare (HEALTH) 3.1 (2021): 1-23. |
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``` |
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``` |
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Jiao, Xiaoqi, et al. "TinyBERT: Distilling BERT for Natural Language Understanding." |
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Findings of the Association for Computational Linguistics: EMNLP 2020. 2020. |
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``` |
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### Contact Information |
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For help or issues using the codes or model (NER module of KAZU) in this repository, please contact WonJin Yoon (wonjin.info (at) gmail.com) or submit a GitHub issue. |
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