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README.md ADDED
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+ ---
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+ language: pt
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+ license: mit
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+ tags:
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+ - msmarco
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+ - t5
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+ - pytorch
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+ - tensorflow
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+ - pt
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+ - pt-br
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+ datasets:
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+ - msmarco
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+ widget:
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+ - text: "Texto de exemplo em português"
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+ inference: false
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+ ---
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+ # mt5-base-multi-msmarco Reranker finetuned on Multi MS MARCO
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+ ## Introduction
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+ mT5-base is a mT5-based model finetuned on a multilingual translated version of MS MARCO passage dataset. This dataset, named Multi MS MARCO, is formed by 12 complete MS MARCO passages collection in 12 different languages.
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+ Further information about the dataset or the translation method can be found on our [Cross-Lingual repository](https://github.com/unicamp-dl/cross-lingual-analysis).
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+
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+ ## Usage
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+ ```python
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+
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+ from transformers import T5Tokenizer, MT5ForConditionalGeneration
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+
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+ model_name = 'unicamp-dl/mt5-base-multi-msmarco'
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+ tokenizer = T5Tokenizer.from_pretrained(model_name)
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+ model = MT5ForConditionalGeneration.from_pretrained(model_name)
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+
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+ ```
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+ # Citation
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+ If you use ptt5-base-msmarco-pt-100k, please cite:
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+
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+ @article{rosa2021cost,
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+ title={A cost-benefit analysis of cross-lingual transfer methods},
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+ author={Rosa, Guilherme Moraes and Bonifacio, Luiz Henrique and de Souza, Leandro Rodrigues and Lotufo, Roberto and Nogueira, Rodrigo},
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+ journal={arXiv preprint arXiv:2105.06813},
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+ year={2021}
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+ }
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