Metadata-Version: 2.1
Name: translation-quality-estimator
Version: 0.1.1
Summary: To estimate the quality of translation
Home-page: https://github.com/theRay07/Translation-Quality-Estimator
Author: Rishav Ray
Author-email: rishavray29@gmail.com
License: MIT
Description: [![PyPI - Python](https://img.shields.io/badge/python-3.6%20|%203.7%20|%203.8-blue.svg)](https://pypi.org/project/translation-quality-estimator/)
        [![PyPI - License](https://img.shields.io/badge/license-MIT-green.svg)](/LICENSE)
        [![PyPI - PyPi](https://img.shields.io/pypi/v/translation-quality-estimator)](https://pypi.org/project/translation-quality-estimator/)
        
        # Translation Quality Estimator
        
        Translation Quality Estimator is a simple but powerful way of estimating the quality of translations in over a hundred languages. It takes two lists of strings as input and returns the cosine similarity scores between their embeddings.
        
        <a name="toc"/></a>
        ## Table of Contents  
        <!--ts-->
           1. [About the Project](#about)  
           2. [Getting Started](#gettingstarted)    
                2.1. [Installation](#installation)    
                2.2. [Basic Usage](#usage)
        <!--te-->
        
        
        <a name="about"/></a>
        ## 1. About the Project
        
        The approach focuses on generating language agnostic state-of-the-art 🤗 transformer embeddings for the list of string pairs (provided as an input) and measures performance by calculating the cosine similarity between the embeddings. The similarity scores range between [0, 1] with higher referring to better quality of translations.
        
        The aim of this project is to create a quick and easy method for estimating the quality of translation of strings.
        
        <a name="gettingstarted"/></a>
        ## 2. Getting Started 
        
        <a name="installation"/></a>
        ###  2.1. Installation
        **[PyTorch 1.2.0](https://pytorch.org/get-started/locally/)** or higher is recommended. If the install below gives an error, please install pytorch first [here](https://pytorch.org/get-started/locally/).
        
        Installation can be done using [pypi](https://pypi.org/project/translation-quality-estimator/)
        
        ```
        pip install translation-quality-estimator
        ```
        
        <a name="usage"/></a>
        ###  2.2. Usage
        
        The most minimal example can be seen below for translation quality estimation between two lists of strings:
        ```python
        from tqe import TQE
        
        lang_1 = ["what are you doing", "what is your name"]
        lang_2 = ["तुम क्या कर रहे हो", "तुम्हारा नाम क्या है"]
        
        model = TQE('LaBSE')
        cos_sim_values = model.fit(lang_1, lang_2)
        print(cos_sim_values)
        ```
        
        **NOTE**: For a full overview of all possible multi-lingual transformer models see [sentence-transformer](https://www.sbert.net/docs/pretrained_models.html).
        I would advise using `'LaBSE'` but you can also test out any `'XLM-R'` or `'Multilingual-BERT'` based models.
        
        ## License
        [MIT](LICENSE)
Keywords: nlp bert translation quality estimator
Platform: UNKNOWN
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
