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  ## Model Specification
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  - This is the **state-of-the-art Twitter NER model (with 74.35\% Entity-Level F1)** on Tweebank V2's NER benchmark (also called `Tweebank-NER`), trained on the corpus combining both Tweebank-NER and WNUT 17 training data.
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- - For more details about the `TweebankNLP` project, please refer to this [our paper](https://arxiv.org/pdf/2201.07281.pdf) and [github](https://github.com/social-machines/TweebankNLP) page. In the paper, it is referred as `HuggingFace-BERTweet (TB2+W17).`
 
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  ## How to use the model
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  ## Model Specification
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  - This is the **state-of-the-art Twitter NER model (with 74.35\% Entity-Level F1)** on Tweebank V2's NER benchmark (also called `Tweebank-NER`), trained on the corpus combining both Tweebank-NER and WNUT 17 training data.
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+ - For more details about the `TweebankNLP` project, please refer to this [our paper](https://arxiv.org/pdf/2201.07281.pdf) and [github](https://github.com/social-machines/TweebankNLP) page.
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+ - In the paper, it is referred as `HuggingFace-BERTweet (TB2+W17).`
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  ## How to use the model
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