hing-gpt-devanagari

HingGPT-Devanagari

HingGPT-Devanagari is a Hindi-English code-mixed GPT model trained on Devanagari text. It is a GPT2 model trained on L3Cube-HingCorpus. <br> [dataset link] (https://github.com/l3cube-pune/code-mixed-nlp)

More details on the dataset, models, and baseline results can be found in our [paper] (https://arxiv.org/abs/2204.08398)

Other models from HingBERT family: <br> <a href="https://huggingface.co/l3cube-pune/hing-bert"> HingBERT </a> <br> <a href="https://huggingface.co/l3cube-pune/hing-mbert"> HingMBERT </a> <br> <a href="https://huggingface.co/l3cube-pune/hing-mbert-mixed"> HingBERT-Mixed </a> <br> <a href="https://huggingface.co/l3cube-pune/hing-mbert-mixed-v2"> HingBERT-Mixed-v2 </a> <br> <a href="https://huggingface.co/l3cube-pune/hing-roberta"> HingRoBERTa </a> <br> <a href="https://huggingface.co/l3cube-pune/hing-roberta-mixed"> HingRoBERTa-Mixed </a> <br> <a href="https://huggingface.co/l3cube-pune/hing-gpt"> HingGPT </a> <br> <a href="https://huggingface.co/l3cube-pune/hing-gpt-devanagari"> HingGPT-Devanagari </a> <br> <a href="https://huggingface.co/l3cube-pune/hing-bert-lid"> HingBERT-LID </a> <br>

@inproceedings{nayak-joshi-2022-l3cube,
    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",
    author = "Nayak, Ravindra  and Joshi, Raviraj",
    booktitle = "Proceedings of the WILDRE-6 Workshop within the 13th Language Resources and Evaluation Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.wildre-1.2",
    pages = "7--12",
}