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@@ -19,14 +19,16 @@ HingBERT is a Hindi-English code-mixed BERT model trained on roman text. It is a
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  More details on the dataset, models, and baseline results can be found in our [paper] (https://arxiv.org/abs/2204.08398)
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  ```
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- @InProceedings{nayak-joshi:2022:WILDRE6,
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- author = {Nayak, Ravindra and Joshi, Raviraj},
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- title = {L3Cube-HingCorpus and HingBERT: A Code Mixed Hindi-English Dataset and BERT Language Models},
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- booktitle = {Proceedings of The WILDRE-6 Workshop within the 13th Language Resources and Evaluation Conference},
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- month = {June},
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- year = {2022},
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- address = {Marseille, France},
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- publisher = {European Language Resources Association},
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- pages = {7--12}
 
 
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  }
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  ```
 
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  More details on the dataset, models, and baseline results can be found in our [paper] (https://arxiv.org/abs/2204.08398)
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  ```
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+ @inproceedings{nayak-joshi-2022-l3cube,
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+ title = "{L}3{C}ube-{H}ing{C}orpus and {H}ing{BERT}: A Code Mixed {H}indi-{E}nglish Dataset and {BERT} Language Models",
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+ author = "Nayak, Ravindra and
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+ Joshi, Raviraj",
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+ booktitle = "Proceedings of the WILDRE-6 Workshop within the 13th Language Resources and Evaluation Conference",
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+ month = jun,
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+ year = "2022",
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+ address = "Marseille, France",
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+ publisher = "European Language Resources Association",
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+ url = "https://aclanthology.org/2022.wildre-1.2",
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+ pages = "7--12",
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  }
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  ```