MindNLP
Installation |
Introduction |
Quick Links |
News 📢
Installation
Install from Pypi
You can install the official version of MindNLP which uploaded to pypi.
pip install mindnlp
Daily build
You can download MindNLP daily wheel from here.
Install from source
To install MindNLP from source, please run:
pip install git+https://github.com/mindspore-lab/mindnlp.git
# or
git clone https://github.com/mindspore-lab/mindnlp.git
cd mindnlp
bash scripts/build_and_reinstall.sh
Version Compatibility
MindNLP version |
MindSpore version |
Supported Python version |
master |
daily build |
>=3.7.5, <=3.9 |
0.1.1 |
>=1.8.1, <=2.0.0 |
>=3.7.5, <=3.9 |
0.2.x |
>=2.1.0 |
>=3.8, <=3.9 |
Introduction
MindNLP is an open source NLP library based on MindSpore. It supports a platform for solving natural language processing tasks, containing many common approaches in NLP. It can help researchers and developers to construct and train models more conveniently and rapidly.
The master branch works with MindSpore master.
Major Features
- Comprehensive data processing: Several classical NLP datasets are packaged into friendly module for easy use, such as Multi30k, SQuAD, CoNLL, etc.
- Friendly NLP model toolset: MindNLP provides various configurable components. It is friendly to customize models using MindNLP.
- Easy-to-use engine: MindNLP simplified complicated training process in MindSpore. It supports Trainer and Evaluator interfaces to train and evaluate models easily.
Quick Links
Supported models
Since there are too many supported models, please check here
License
This project is released under the Apache 2.0 license.
Feedbacks and Contact
The dynamic version is still under development, if you find any issue or have an idea on new features, please don't hesitate to contact us via Github Issues.
Acknowledgement
MindSpore is an open source project that welcome any contribution and feedback.
We wish that the toolbox and benchmark could serve the growing research
community by providing a flexible as well as standardized toolkit to reimplement existing methods
and develop their own new semantic segmentation methods.
Citation
If you find this project useful in your research, please consider citing:
@misc{mindnlp2022,
title={{MindNLP}: a MindSpore NLP library},
author={MindNLP Contributors},
howpublished = {\url{https://github.com/mindlab-ai/mindnlp}},
year={2022}
}