Metadata-Version: 2.1
Name: text-tagging-model
Version: 0.1.4
Summary: Here we collected some online and offline models for text tagging.
Author: Pavel Kochkin
Author-email: kochkin27@gmail.com
Requires-Python: >=3.9,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: coloredlogs (>=15.0.1,<16.0.0)
Requires-Dist: fasttext-wheel (>=0.9.2,<0.10.0)
Requires-Dist: nltk (>=3.8.1,<4.0.0)
Requires-Dist: numpy (>=1.24.4,<2.0.0)
Requires-Dist: pymorphy2 (>=0.9.1,<0.10.0)
Requires-Dist: rake-nltk (>=1.0.6,<2.0.0)
Requires-Dist: rouge (>=1.0.1,<2.0.0)
Requires-Dist: scikit-learn (>=1.4.1.post1,<2.0.0)
Requires-Dist: sentence-transformers (>=2.6.1,<3.0.0)
Requires-Dist: sentencepiece (>=0.2.0,<0.3.0)
Requires-Dist: tqdm (>=4.66.2,<5.0.0)
Requires-Dist: transformers (>=4.39.3,<5.0.0)
Description-Content-Type: text/markdown

<h1 align="center" id="title">Text Tagging Model</h1>

<p id="description">Here we collected some online and offline models for text tagging.</p>

<h2>🚀 Demo</h2>

[https://colab.research.google.com/drive/1xlevLnqxd\_wCtXunGgf\_pSrdkz85jt49?usp=sharing](https://colab.research.google.com/drive/1xlevLnqxd_wCtXunGgf_pSrdkz85jt49?usp=sharing)



<h2>🧐 Features</h2>

Here're some of the project's best features:

*   Online model: Rake Based Model with 10-20 it/sec
*   Offline models: Bart based model with summarisation or attention. 1-5 it/sec

<h2>🛠️ Installation Steps:</h2>

<p>1. Installation</p>

```
pip install text-tagging-model
```

<p>2. import</p>

```
from text_tagging_model.models.rake_based_model import TagsExtractor
```

<p>3. Init tagger</p>

```
tagger = TagsExtractor()
```

<p>4. Get tags</p>

```
tagger.extract(some_text)
```

