README.md

---
language: pt
license: mit
tags:
- msmarco
- miniLM
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- msmarco
widget:
- text: "Texto de exemplo em português"
inference: false
---
# multilingual-MiniLM-L6-v2-en-pt-msmarco Reranker finetuned on mMARCO
## Introduction
multilingual-MiniLM-L6-v2-en-pt-msmarco is a multilingual miniLM-based model finetuned on a bilingual version of MS MARCO passage dataset. This bilingual dataset version is formed by the original MS MARCO dataset (in English) and a Portuguese translated version.
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).
## Usage
```python
from transformers import AutoTokenizer, AutoModel

model_name = 'unicamp-dl/multilingual-MiniLM-L6-v2-en-pt-msmarco'
tokenizer  = AutoTokenizer.from_pretrained(model_name)
model      = AutoModel.from_pretrained(model_name)

```
# Citation
If you use mt5-base-en-pt-msmarco, please cite:

    @article{rosa2021cost,
      title={A cost-benefit analysis of cross-lingual transfer methods},
      author={Rosa, Guilherme Moraes and Bonifacio, Luiz Henrique and de Souza, Leandro Rodrigues and Lotufo, Roberto and Nogueira, Rodrigo},
      journal={arXiv preprint arXiv:2105.06813},
      year={2021}
    }