Metadata-Version: 2.1
Name: ilmulti
Version: 0.0.0
Summary: Multilingual Text Tooling around Indian Languages
Home-page: https://github.com/jerinphilip/ilmulti
Author: Jerin Philip
Author-email: jerin.philip@research.iiit.ac.in
License: MIT
Description: 
        # ilmulti
        
        This repository houses tooling used to create the models on the
        leaderboard of WAT-Tasks. We provide wrappers to models which are
        trained via [pytorch/fairseq](http://github.com/pytorch/fairseq) to
        translate. Installation and usage intructions are provided below.
        
        * **Training**: We use a separate fork of
          [pytorch/fairseq](http://github.com/pytorch/fairseq) at
          [jerinphilip/fairseq-ilmt](http://github.com/jerinphilip/fairseq-ilmt) for
          training to optimize for our cluster and to plug and play data
          easily.
        
        * **Pretrained Models and Other Resources**: 
          [preon.iiit.ac.in/~jerin/bhasha](http://preon.iiit.ac.in/~jerin/bhasha)
        
        
        ## Installation
        
        The code is tested to work with the fairseq-fork which is branched from v0.7.2 and torch version 1.0.0.
        
        ```bash
        # --user is optional
        python3 -m pip install -r requirements.txt --user  
        python3 setup.py install --user 
        
        ```
        
        **Downloading Models**: The script
        [`scripts/download-and-setup-models.sh`](./scripts/download-and-setup-models.sh)
        downloads the model and dictionary files required for running
        [`examples/mm_all.py`](./examples/mm_all.py). Which models to download
        can be configured in the script.
        
        A working example using the wrappers in this code can be found in this [Colab Notebook](https://colab.research.google.com/drive/1KOvjawhzPXOQ6RLlFBFeInkuuR0QAWTK?usp=sharing).
        
        ## Usage
        
        ```python3
        from ilmulti.translator import from_pretrained
        
        translator = from_pretrained(tag='mm-all')
        sample = translator("The quick brown fox jumps over the lazy dog", tgt_lang='hi')
        ```
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown
