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  >>> from transformers import AutoTokenizer, AutoModelForMaskedLM
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  >>> tokenizer = AutoTokenizer.from_pretrained("mynoguti/BERTimbau_Legal")
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  >>> model = AutoModelForMaskedLM.from_pretrained("mynoguti/BERTimbau_Legal")
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  >>> from transformers import AutoTokenizer, AutoModelForMaskedLM
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  >>> tokenizer = AutoTokenizer.from_pretrained("mynoguti/BERTimbau_Legal")
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  >>> model = AutoModelForMaskedLM.from_pretrained("mynoguti/BERTimbau_Legal")
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+ ```
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+
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+ **Citation:**
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+ ```
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+ @inproceedings{Noguti_2023,
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+ title={A Small Claims Court for the NLP: Judging Legal Text Classification Strategies With Small Datasets},
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+ url={http://dx.doi.org/10.1109/SMC53992.2023.10394189},
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+ DOI={10.1109/smc53992.2023.10394189},
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+ booktitle={2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)},
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+ publisher={IEEE},
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+ author={Noguti, Mariana and Vellasques, Eduardo and Oliveira, Luiz S.},
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+ year={2023},
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+ month=oct, pages={1840–1845} }
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  ```