# mMiniLM-L6 Reranker finetuned on English MS MARCO
## Introduction
mMiniLM-L6-v2-en-msmarco is a multilingual miniLM-based model fine-tuned on English MS MARCO passage dataset. Further information about the dataset or the translation method can be found on our [**mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset**](https://arxiv.org/abs/2108.13897) and [mMARCO](https://github.com/unicamp-dl/mMARCO) repository.
## Usage
```python
from transformers import AutoTokenizer, AutoModel

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

```
# Citation
If you use mMiniLM-L6-v2-en-msmarco, please cite:

    @misc{bonifacio2021mmarco,
      title={mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset}, 
      author={Luiz Henrique Bonifacio and Vitor Jeronymo and Hugo Queiroz Abonizio and Israel Campiotti and Marzieh Fadaee and  and Roberto Lotufo and Rodrigo Nogueira},
      year={2021},
      eprint={2108.13897},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}


{"language": "pt", "license": "mit", "tags": ["msmarco", "miniLM", "pytorch", "tensorflow", "en"], "datasets": ["msmarco"], "widget": [{"text": "Texto de exemplo em portugu\u00c3\u00aas"}], "inference": false}
transformers pytorch xlm-roberta text-classification msmarco miniLM tensorflow en pt dataset:msmarco arxiv:2108.13897 license:mit autotrain_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #text-classification #msmarco #miniLM #tensorflow #en #pt #dataset-msmarco #arxiv-2108.13897 #license-mit #autotrain_compatible #region-us 

# mMiniLM-L6 Reranker finetuned on English MS MARCO
## Introduction
mMiniLM-L6-v2-en-msmarco is a multilingual miniLM-based model fine-tuned on English MS MARCO passage dataset. Further information about the dataset or the translation method can be found on our mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset and mMARCO repository.
## Usage

If you use mMiniLM-L6-v2-en-msmarco, please cite:

    @misc{bonifacio2021mmarco,
      title={mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset}, 
      author={Luiz Henrique Bonifacio and Vitor Jeronymo and Hugo Queiroz Abonizio and Israel Campiotti and Marzieh Fadaee and  and Roberto Lotufo and Rodrigo Nogueira},
      year={2021},
      eprint={2108.13897},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}


# mMiniLM-L6 Reranker finetuned on English MS MARCO ## Introduction
mMiniLM-L6-v2-en-msmarco is a multilingual miniLM-based model fine-tuned on English MS MARCO passage dataset. Further information about the dataset or the translation method can be found on our mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset and mMARCO repository. ## Usage

If you use mMiniLM-L6-v2-en-msmarco, please cite:

    @misc{bonifacio2021mmarco,
      title={mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset}, 
      author={Luiz Henrique Bonifacio and Vitor Jeronymo and Hugo Queiroz Abonizio and Israel Campiotti and Marzieh Fadaee and  and Roberto Lotufo and Rodrigo Nogueira},
      year={2021},
      eprint={2108.13897},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
TAGS
#transformers #pytorch #xlm-roberta #text-classification #msmarco #miniLM #tensorflow #en #pt #dataset-msmarco #arxiv-2108.13897 #license-mit #autotrain_compatible #region-us 
 # mMiniLM-L6 Reranker finetuned on English MS MARCO ## Introduction
mMiniLM-L6-v2-en-msmarco is a multilingual miniLM-based model fine-tuned on English MS MARCO passage dataset. Further information about the dataset or the translation method can be found on our mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset and mMARCO repository. ## Usage

If you use mMiniLM-L6-v2-en-msmarco, please cite:

    @misc{bonifacio2021mmarco,
      title={mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset}, 
      author={Luiz Henrique Bonifacio and Vitor Jeronymo and Hugo Queiroz Abonizio and Israel Campiotti and Marzieh Fadaee and  and Roberto Lotufo and Rodrigo Nogueira},
      year={2021},
      eprint={2108.13897},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
passage: TAGS
#transformers #pytorch #xlm-roberta #text-classification #msmarco #miniLM #tensorflow #en #pt #dataset-msmarco #arxiv-2108.13897 #license-mit #autotrain_compatible #region-us 
# mMiniLM-L6 Reranker finetuned on English MS MARCO## Introduction
mMiniLM-L6-v2-en-msmarco is a multilingual miniLM-based model fine-tuned on English MS MARCO passage dataset. Further information about the dataset or the translation method can be found on our mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset and mMARCO repository.## Usage

If you use mMiniLM-L6-v2-en-msmarco, please cite:

    @misc{bonifacio2021mmarco,
      title={mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset}, 
      author={Luiz Henrique Bonifacio and Vitor Jeronymo and Hugo Queiroz Abonizio and Israel Campiotti and Marzieh Fadaee and  and Roberto Lotufo and Rodrigo Nogueira},
      year={2021},
      eprint={2108.13897},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}