transformers pytorch IndicTrans text2text-generation indictrans2 translation ai4bharat multilingual custom_code as bn brx doi en gom gu hi kn ks kas mai ml mr mni mnb ne or pa sa sat sd snd ta te ur dataset:flores-200 dataset:IN22-Gen dataset:IN22-Conv license:mit autotrain_compatible region:us
---
datasets:
- flores-200
- IN22-Gen
- IN22-Conv
language:
- as
- bn
- brx
- doi
- en
- gom
- gu
- hi
- kn
- ks
- kas
- mai
- ml
- mr
- mni
- mnb
- ne
- or
- pa
- sa
- sat
- sd
- snd
- ta
- te
- ur
license: mit
metrics:
- bleu
- chrf
- chrf++
- comet
tags:
- indictrans2
- translation
- ai4bharat
- multilingual
language_details: asm_Beng, ben_Beng, brx_Deva, doi_Deva, eng_Latn, gom_Deva, guj_Gujr,
  hin_Deva, kan_Knda, kas_Arab, kas_Deva, mai_Deva, mal_Mlym, mar_Deva, mni_Beng,
  mni_Mtei, npi_Deva, ory_Orya, pan_Guru, san_Deva, sat_Olck, snd_Arab, snd_Deva,
  tam_Taml, tel_Telu, urd_Arab
inference: false
---

# IndicTrans2

This is the model card of IndicTrans2 Indic-En Distilled 200M variant.

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.

### 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.


### Citation

If you consider using our work then please cite using:

```
@article{ai4bharat2023indictrans2,
  title   = {IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages},
  author  = {AI4Bharat and Jay Gala and Pranjal A. Chitale and Raghavan AK and Sumanth Doddapaneni and Varun Gumma and Aswanth Kumar and Janki Nawale and Anupama Sujatha and Ratish Puduppully and Vivek Raghavan and Pratyush Kumar and Mitesh M. Khapra and Raj Dabre and Anoop Kunchukuttan},
  year    = {2023},
  journal = {arXiv preprint arXiv: 2305.16307}
}
```
