l3cube-pune
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README.md
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---
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language:
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- hi
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- en
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- multilingual
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license: cc-by-4.0
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tags:
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- hi
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- en
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- codemix
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datasets:
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- L3Cube-HingCorpus
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---
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## HingBERT-Mixed-v2
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HingBERT-Mixed-v2 is a Hindi-English code-mixed BERT model trained on roman + devanagari text. It is a base MuRIL model fine-tuned on mixed script L3Cube-HingCorpus.
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<br>
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[dataset link] (https://github.com/l3cube-pune/code-mixed-nlp)
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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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Other models from HingBERT family: <br>
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<a href="https://huggingface.co/l3cube-pune/hing-bert"> HingBERT </a> <br>
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<a href="https://huggingface.co/l3cube-pune/hing-mbert"> HingMBERT </a> <br>
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<a href="https://huggingface.co/l3cube-pune/hing-mbert-mixed"> HingBERT-Mixed </a> <br>
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<a href="https://huggingface.co/l3cube-pune/hing-roberta"> HingRoBERTa </a> <br>
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<a href="https://huggingface.co/l3cube-pune/hing-roberta-mixed"> HingRoBERTa-Mixed </a> <br>
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<a href="https://huggingface.co/l3cube-pune/hing-gpt"> HingGPT </a> <br>
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<a href="https://huggingface.co/l3cube-pune/hing-gpt-devanagari"> HingGPT-Devanagari </a> <br>
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<a href="https://huggingface.co/l3cube-pune/hing-bert-lid"> HingBERT-LID </a> <br>
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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 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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```
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