Persian-Word-Embedding

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Persian-Word-Embedding

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Persian word embedding ( نشاننده واژه ها فارسی | تعبیه سازی کلمات فارسی )

Persian-Word-Embedding 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

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# ``*still under construction``
<p align="center">
  <img align="center" width="304" height="228" src="/assets/ginger-cat-productive-work.png">
</p>

<h1 align="center">Persian Word Embedding</h1>

### ``Word is a word embedding model?``
<img align="right" width="261.75" height="228" src="/assets/flamenco-downloading-1.png">

Word embedding is one of the most popular representation of document vocabulary. It is capable of capturing context of a word in a document, semantic and syntactic similarity, relation with other words, etc.

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### ``So what now?``

Hmm not very important but maybe the only place you can find all word embedding for Persian to ``Train`` or just download the ``Pretrained`` version and of course one important thing is that, here I collect current best Models (2019) and I made a ``Lite`` version of them to use in your JS or Android or C# or ... Application without using Online API or...

> Important note: some models currently have pretrained version for Persian so I just made them lite

### ``Corpus?`` Wikipedia!
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#### Where to Download ``Wikipedia`` Corpus?
You can see backup status of Wikipedia in each language [here](https://dumps.wikimedia.org/backup-index-bydb.html). And you can see backup versions you can download for Persian Wikipedia [here](https://dumps.wikimedia.org/fawiki/). Choose "latest" because we want to use the newest version. And we need to download [fawiki-latest-pages-articles-multistream.xml.bz2](https://dumps.wikimedia.org/fawiki/latest/fawiki-latest-pages-articles-multistream.xml.bz2) in the files.

#### Here is some others Corpus to Download
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### Models
  - #Fasttext
  FastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices.

### Project status
- [ ] [Google’s Universal Sentence Encoder](http://google.com) (This one is not Public Available)
  - [ ] Train.py
  - [ ] Train.ipynb
  - [ ] Model.bin
  - [ ] Model_Lite.bin
  - [ ] Model.vec
  - [ ] Model_Lite.vec
- [x] [FasTText](https://github.com/ashalogic/Persian-Word-Embedding/tree/master/Fasttext)
  - [ ] Train.py
  - [ ] Train.ipynb
  - [x] Model.bin
  - [ ] Model_Lite.bin
  - [x] Model.vec
  - [ ] Model_Lite.vec
- [ ] [ELMo](https://github.com/ashalogic/Persian-Word-Embedding/tree/master/Elmo)
  - [ ] Train.py
  - [ ] Train.ipynb
  - [ ] Model.bin
  - [ ] Model_Lite.bin
  - [ ] Model.vec
  - [ ] Model_Lite.vec
- [ ] [Word2Vec](https://github.com/ashalogic/Persian-Word-Embedding/tree/master/Word2vec)
  - [ ] Train.py
  - [ ] Train.ipynb
  - [ ] Model.bin
  - [ ] Model_Lite.bin
  - [ ] Model.vec
  - [ ] Model_Lite.vec
- [ ] [Glove](https://github.com/ashalogic/Persian-Word-Embedding/tree/master/Glove)
  - [ ] Train.py
  - [ ] Train.ipynb
  - [ ] Model.bin
  - [ ] Model_Lite.bin
  - [ ] Model.vec
  - [ ] Model_Lite.vec

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Persian-Word-Embedding 최신버젼 다운로드

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