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fastNLP
FastNLP is a modular Natural Language Processing system based on PyTorch, built for fast development of NLP models.
A deep learning NLP model is the composition of three types of modules:
| module type | functionality | example |
| encoder | encode the input into some abstract representation | embedding, RNN, CNN, transformer |
| aggregator | aggregate and reduce information | self-attention, max-pooling |
| decoder | decode the representation into the output | MLP, CRF |
For example:
Requirements
- Python>=3.6
- numpy>=1.14.2
- torch>=0.4.0
- tensorboardX
- tqdm>=4.28.1
Resources
Installation
Run the following commands to install fastNLP package.
pip install fastNLP
Models
fastNLP implements different models for variant NLP tasks.
Each model has been trained and tested carefully.
Check out models' performance, usage and source code here.
Project Structure
| fastNLP | an open-source NLP library |
| fastNLP.api | APIs for end-to-end prediction |
| fastNLP.core | data representation & train/test procedure |
| fastNLP.models | a collection of NLP models |
| fastNLP.modules | a collection of PyTorch sub-models/components/wheels |
| fastNLP.io | readers & savers |