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README.md
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@@ -3,6 +3,7 @@ This model repository presents "TinyPubMedBERT", a distillated [PubMedBERT (Gu e
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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 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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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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