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--- |
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language: |
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- as |
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- bn |
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- brx |
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- doi |
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- en |
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- gom |
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- gu |
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- hi |
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- kn |
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- ks |
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- kas |
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- mai |
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- ml |
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- mr |
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- mni |
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- mnb |
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- ne |
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- or |
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- pa |
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- sa |
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- sat |
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- sd |
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- snd |
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- ta |
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- te |
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- ur |
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language_details: >- |
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asm_Beng, ben_Beng, brx_Deva, doi_Deva, eng_Latn, gom_Deva, guj_Gujr, |
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hin_Deva, kan_Knda, kas_Arab, kas_Deva, mai_Deva, mal_Mlym, mar_Deva, |
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mni_Beng, mni_Mtei, npi_Deva, ory_Orya, pan_Guru, san_Deva, sat_Olck, |
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snd_Arab, snd_Deva, tam_Taml, tel_Telu, urd_Arab |
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tags: |
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- indictrans2 |
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- translation |
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- ai4bharat |
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- multilingual |
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license: mit |
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datasets: |
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- flores-200 |
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- IN22-Gen |
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- IN22-Conv |
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metrics: |
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- bleu |
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- chrf |
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- chrf++ |
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- comet |
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inference: false |
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--- |
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# IndicTrans2 |
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This is the model card of IndicTrans2 En-Indic Distilled 200M variant. |
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Please refer to [section 7.6: Distilled Models](https://openreview.net/forum?id=vfT4YuzAYA) in the TMLR submission for further details on model training, data and metrics. |
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### Usage Instructions |
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Please refer to the [github repository](https://github.com/AI4Bharat/IndicTrans2/tree/main/huggingface_inference) for a detail description on how to use HF compatible IndicTrans2 models for inference. |
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**Note: IndicTrans2 is not compatible with AutoTokenizer, therefore we provide [IndicTransTokenizer](https://github.com/VarunGumma/IndicTransTokenizer)** |
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### Citation |
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If you consider using our work then please cite using: |
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``` |
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@article{gala2023indictrans, |
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title={IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages}, |
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author={Jay Gala and Pranjal A Chitale and A K Raghavan and Varun Gumma and Sumanth Doddapaneni and Aswanth Kumar M and Janki Atul Nawale and Anupama Sujatha and Ratish Puduppully and Vivek Raghavan and Pratyush Kumar and Mitesh M Khapra and Raj Dabre and Anoop Kunchukuttan}, |
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journal={Transactions on Machine Learning Research}, |
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issn={2835-8856}, |
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year={2023}, |
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url={https://openreview.net/forum?id=vfT4YuzAYA}, |
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note={} |
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} |
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``` |
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|
