
# IndicTrans2

This is the model card of IndicTrans2 Indic-Indic 1B variant adapted after stitching Indic-En 1B and En-Indic 1B variants.

Please refer to the [blog](https://ai4bharat.iitm.ac.in/blog/indictrans2-m2m/) for further details on model training, data and metrics.

### Usage Instructions

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.

**Note: IndicTrans2 is not compatible with AutoTokenizer, therefore we provide [IndicTransTokenizer](https://github.com/VarunGumma/IndicTransTokenizer)**


### Citation

If you consider using our work then please cite using:

```
@article{gala2023indictrans,
title={IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages},
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},
journal={Transactions on Machine Learning Research},
issn={2835-8856},
year={2023},
url={https://openreview.net/forum?id=vfT4YuzAYA},
note={}
}
```
{"language": ["as", "bn", "brx", "doi", "gom", "gu", "hi", "kn", "ks", "mai", "ml", "mr", "mni", "ne", "or", "pa", "sa", "sat", "snd", "ta", "te", "ur"], "license": "mit", "tags": ["indictrans2", "translation", "ai4bharat", "multilingual"], "datasets": ["flores-200", "IN22-Gen", "IN22-Conv"], "metrics": ["bleu", "chrf", "chrf++", "comet"], "language_details": "asm_Beng, ben_Beng, brx_Deva, doi_Deva, gom_Deva, guj_Gujr, hin_Deva, kan_Knda, kas_Arab, mai_Deva, mal_Mlym, mar_Deva, mni_Mtei, npi_Deva, ory_Orya, pan_Guru, san_Deva, sat_Olck, snd_Deva, tam_Taml, tel_Telu, urd_Arab", "inference": false}
transformers pytorch IndicTrans text2text-generation indictrans2 translation ai4bharat multilingual custom_code as bn brx doi gom gu hi kn ks mai ml mr mni ne or pa sa sat snd ta te ur dataset:flores-200 dataset:IN22-Gen dataset:IN22-Conv license:mit autotrain_compatible region:us