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92 lines
2.4 KiB
Markdown
92 lines
2.4 KiB
Markdown
# fastNLP
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[![Build Status](https://travis-ci.org/fastnlp/fastNLP.svg?branch=master)](https://travis-ci.org/fastnlp/fastNLP)
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[![codecov](https://codecov.io/gh/fastnlp/fastNLP/branch/master/graph/badge.svg)](https://codecov.io/gh/fastnlp/fastNLP)
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[![PyPI version](https://badge.fury.io/py/fastNLP.svg)](https://badge.fury.io/py/fastNLP)
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![Hex.pm](https://img.shields.io/hexpm/l/plug.svg)
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[![Documentation Status](https://readthedocs.org/projects/fastnlp/badge/?version=latest)](http://fastnlp.readthedocs.io/?badge=latest)
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FastNLP is a modular Natural Language Processing system based on PyTorch, built for fast development of NLP models.
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*Very sad day for all of us. @FengZiYjun is no more with us. May his soul rest in peace. We will miss you very very much!*
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A deep learning NLP model is the composition of three types of modules:
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<table>
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<tr>
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<td><b> module type </b></td>
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<td><b> functionality </b></td>
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<td><b> example </b></td>
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</tr>
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<tr>
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<td> encoder </td>
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<td> encode the input into some abstract representation </td>
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<td> embedding, RNN, CNN, transformer
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</tr>
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<tr>
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<td> aggregator </td>
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<td> aggregate and reduce information </td>
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<td> self-attention, max-pooling </td>
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</tr>
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<tr>
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<td> decoder </td>
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<td> decode the representation into the output </td>
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<td> MLP, CRF </td>
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</tr>
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</table>
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For example:
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![](docs/source/figures/text_classification.png)
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## Requirements
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- Python>=3.6
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- numpy>=1.14.2
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- torch>=0.4.0
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- tensorboardX
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- tqdm>=4.28.1
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## Resources
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- [Tutorials](https://github.com/fastnlp/fastNLP/tree/master/tutorials)
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- [Documentation](https://fastnlp.readthedocs.io/en/latest/)
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- [Source Code](https://github.com/fastnlp/fastNLP)
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## Installation
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Run the following commands to install fastNLP package.
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```shell
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pip install fastNLP
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```
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## Project Structure
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<table>
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<tr>
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<td><b> fastNLP </b></td>
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<td> an open-source NLP library </td>
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</tr>
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<tr>
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<td><b> fastNLP.api </b></td>
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<td> APIs for end-to-end prediction </td>
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</tr>
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<tr>
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<td><b> fastNLP.core </b></td>
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<td> data representation & train/test procedure </td>
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</tr>
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<tr>
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<td><b> fastNLP.models </b></td>
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<td> a collection of NLP models </td>
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</tr>
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<tr>
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<td><b> fastNLP.modules </b></td>
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<td> a collection of PyTorch sub-models/components/wheels </td>
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</tr>
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<tr>
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<td><b> fastNLP.io </b></td>
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<td> readers & savers </td>
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</tr>
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</table>
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