Metadata-Version: 2.1
Name: nlprep
Version: 0.1.45
Summary: Download and pre-processing data for nlp tasks
Home-page: https://github.com/voidful/nlprep
Author: Voidful
Author-email: voidful.stack@gmail.com
License: UNKNOWN
Description: <p align="center">
            <br>
            <img src="https://raw.githubusercontent.com/voidful/NLPrep/master/docs/img/nlprep.png" width="400"/>
            <br>
        </p>
        <p align="center">
            <a href="https://pypi.org/project/nlprep/">
                <img alt="PyPI" src="https://img.shields.io/pypi/v/nlprep">
            </a>
            <a href="https://github.com/voidful/NLPrep">
                <img alt="Download" src="https://img.shields.io/pypi/dm/nlprep">
            </a>
            <a href="https://github.com/voidful/NLPrep">
                <img alt="Build" src="https://img.shields.io/github/workflow/status/voidful/NLPrep/Python package">
            </a>
            <a href="https://github.com/voidful/NLPrep">
                <img alt="Last Commit" src="https://img.shields.io/github/last-commit/voidful/NLPrep">
            </a>
        </p>
        
        ## Feature  
        - handle over 100 dataset  
        - generate statistic report about processed dataset  
        - support many pre-processing ways  
        - Provide a panel for entering your parameters at runtime  
        - easy to adapt your own dataset and pre-processing utility  
        
        # Online Explorer
        [https://voidful.github.io/NLPrep-Datasets/](https://voidful.github.io/NLPrep-Datasets/)   
        
        # Documentation
        Learn more from the [docs](https://voidful.github.io/NLPrep/).  
        
        ## Quick Start
        ### Installing via pip
        ```bash
        pip install nlprep
        ```
        ### get one of the dataset
        ```bash
        nlprep --dataset clas_udicstm --outdir sentiment
        ```
        
        **You can also try nlprep in Google Colab: [![Google Colab](https://colab.research.google.com/assets/colab-badge.svg "nlprep")](https://colab.research.google.com/drive/1EfVXa0O1gtTZ1xEAPDyvXMnyjcHxO7Jk?usp=sharing)**
        
        ## Overview
        ```
        $ nlprep
        arguments:
          --dataset     which dataset to use     
          --outdir      processed result output directory       
          
        optional arguments:
          -h, --help    show this help message and exit
          --util        data preprocessing utility, multiple utility are supported 
          --cachedir    dir for caching raw dataset
          --infile      local dataset path
          --report      generate a html statistics report
        ```
        
        ## Contributing
        Thanks for your interest.There are many ways to contribute to this project. Get started [here](https://github.com/voidful/nlprep/blob/master/CONTRIBUTING.md).
        
        ## License ![PyPI - License](https://img.shields.io/github/license/voidful/nlprep)
        
        * [License](https://github.com/voidful/nlprep/blob/master/LICENSE)
        
        ## Icons reference
        Icons modify from <a href="https://www.flaticon.com/authors/darius-dan" title="Darius Dan">Darius Dan</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a>    
        Icons modify from <a href="https://www.flaticon.com/authors/freepik" title="Freepik">Freepik</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a>    
        
Keywords: nlp tfkit classification generation tagging deep learning machine reading
Platform: UNKNOWN
Description-Content-Type: text/markdown
