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Natural Language Processing (NLP) library for Urdu language.

Project description

Urduhack: A Python NLP library for Urdu language

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Urduhack is a NLP library for urdu language. It comes with a lot of battery included features to help you process Urdu data in the easiest way possible.

Our Goal

  • Academic users Easier experimentation to prove their hypothesis without coding from scratch.
  • NLP beginners Learn how to build an NLP project with production level code quality.
  • NLP developers Build a production level application within minutes.

🔥 Features Support

  • Normalization
  • Tokenization
  • Preprocessing
  • Pipeline Module
  • Models
    • Pos tagger
    • Sentimental analysis
    • Sentence classification
    • Documents classification
    • Name entity recognition
    • Image to text
    • Speech to text
  • Datasets loader

🛠 Installation

Urduhack officially supports Python 3.6–3.7, and runs great on PyPy.

Installing with tensorflow cpu version.

$ pip install urduhack[tf]

Installing with tensorflow gpu version.

$ pip install urduhack[tf-gpu]


import urduhack

# Downloading models

nlp = urduhack.Pipeline()
text = ""
doc = nlp(text)

for sentence in doc.sentences:
    for word in sentence.words:

🔗 Documentation

Fantastic documentation is available at

Installation How to install Urduhack and download models
Quickstart New to Urduhack? Here's everything you need to know!
API Reference The detailed reference for Urduhack's API.

How to Contribute

  1. Check for open issues or open a fresh issue to start a discussion around a feature idea or a bug. There is a Contributor Friendly tag for issues that should be ideal for people who are not very familiar with the codebase yet.
  2. Write a test which shows that the bug was fixed or that the feature works as expected.
  3. Send a pull request and bug the maintainer until it gets merged and published. :)

👍 Contributors

Special thanks to everyone who contributed to getting the UrduHack to the current state.

Backers Backers on Open Collective

Thank you to all our backers! 🙏 [Become a backer]

Sponsors Sponsors on Open Collective

Support this project by becoming a sponsor. [Become a sponsor]

📝 Copyright and license

Code released under the MIT License.

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