Metadata-Version: 2.1
Name: aamraz
Version: 0.0.1
Summary: This project is a collection of Natural Language Processing tools for Kurdish Language.
Home-page: https://github.com/MohammadDevelop/Aamraz
Author: Mohammad Mahmoodi Varnamkhasti
Author-email: research@amzmohammad.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy >=2.1.0
Requires-Dist: fasttext >=0.9.3

# Aamraz - Kurdish NLP collection

- [Overview](#overview)
- [Features](#features)
- [Installation](#installation)
- [Pre-trained Models](#PretrainedModels)
- [Usage](#usage)

## Overview
Aamraz which is written "ئامراز" in kurdish script means "instrument". This project is a collection of Natural Language Processing tools for Kurdish Language.

## Base Features
- **Word Embedding:** Creates vector representations of words.

## Tools

## Installation

## PretrainedModels

some useful pre-trained Models:

| **Model**                             | Description                                                                                                                                                                                                   |**Size** |
|:--------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------- |
| [**FastText WordEmbedding**](https://mega.nz/file/yNYVnDgQ#xoPydAT_75vEu0jXQIFxetFtFScdyFJpmCsAwjVUAzQ)        | Model trained using [FastText](https://fasttext.cc/) method on our own Corpus.
 This is bot the fasttext & skip-gram model itself ([fasttext model](https://fasttext.cc/docs/en/pretrained-vectors.html). |~ 5 GB   |
| [**FastText WordEmbedding - Lite**]() | Model trained using [FastText](https://fasttext.cc/) method on our own Corpus.
 This is bot the fasttext & skip-gram model itself ([fasttext model](https://fasttext.cc/docs/en/pretrained-vectors.html). |~ 5 GB   |

## Usage

# Creative Commons Attribution 4.0 International (CC BY 4.0)

This license lets others distribute, remix, adapt, and build upon your work, even commercially, as long as they credit you for the original creation. 

To view a copy of this license, visit: 
https://creativecommons.org/licenses/by/4.0/
