Integrate IndicTrans2 models and tokenizer into HF Transformers

### Model description [IndicTrans2 ](https://openreview.net/forum?id=vfT4YuzAYA)is a multilingual transformer model developed by AI4Bharat, and is available in 3 flavors: `indic-en`, `en-indic` and `indic-indic`. Each flavor has 2 versions, a large 1B model, and a distilled 200M model. The architecture is a standard transformer, very similar to NLLB and M2M models. However, the major difference is the vocabularies of the encoder and decoder and not shared, as they require different languages. Unlike, NLLB and M2M models, IndicTrans2 required specific preprocessing for the inputs. Hence a [custom processor class has been developed](https://github.com/VarunGumma/IndicTransTokenizer), and is required for training/inference. More examples can be found in the aforementioned repository. ### Open source status - [X] The model implementation is available - [X] The model weights are available ### Provide useful links for the implementation Authors: @AI4Bharat @jaygala24 @PranjalChitale @oneraghavan @VarunGumma @sumanthd17 @prajdabre @anoopkunchukuttan Official GitHub Repository: [AI4Bharat/IndicTrans2](https://github.com/ai4bharat/IndicTrans2) The HF compatible models and tokenizer are available here as of now: - [indictrans2-en-indic-1B](https://huggingface.co/ai4bharat/indictrans2-en-indic-1B) - [indictrans2-en-indic-dist-200M](https://huggingface.co/ai4bharat/indictrans2-en-indic-dist-200M) - [indictrans2-indic-en-dist-200M](https://huggingface.co/ai4bharat/indictrans2-indic-en-dist-200M) - [indictrans2-indic-en-1B](https://huggingface.co/ai4bharat/indictrans2-indic-en-1B) - [indictrans2-indic-indic-1B](https://huggingface.co/ai4bharat/indictrans2-indic-indic-1B) - [indictrans2-indic-indic-dist-320M](https://huggingface.co/ai4bharat/indictrans2-indic-indic-dist-320M)