nlpipes 0.1.16

Text Classification with Transformers

Text Classification with Transformers

Documentation • References

Overview

NLPipes is designed for people unfamiliar with Transformers who want an end to end solution to solve practical text classification problems, including:

• Single-label classification: A typical use case is sentiment detection where one want to detect the overall sentiment polarity (e.g., positive, neutral, negative) in a review.
• Multi-labels classification: A typical use case is aspect categories detection where one want to detect the multiple aspects mentionned in a review (e.g., product_quality, delivery_time, price, ...).
• Aspect-based classification [Not yet implemented]: A typical use case is aspect based sentiment analysis where one want to detect each aspect categories mentionned in a review along his assocated sentiment polarity (e.g., product_quality: neutral, delivery_time: negative, price: positive, ...).

NLPipes expose a Model API that provide a simple abstraction for all text classification tasks. The library maintain a common usage pattern across models (train, evaluate, predict, save) with also a clear and consistent data structure (python lists as inputs/outputs data). Most of NLPipes functionnalities are based on callbacks functions. This provide a modular architecture that allow new ideas to be implemented without having to increase the complexity of the core.

Built with

NLPipes is built with TensorFlow and HuggingFace Transformers:

• TensorFlow: An end-to-end open source deep learning framework
• Transformers: An general-purpose open-sources library for transformers-based architectures

Getting Started

Installation

1. Create a virtual environment

python3 -m venv nlpipesenv
source nlpipesenv/bin/activate

2. Install the package

pip install nlpipes

Tutorials

Here are some examples on open datasets that show how to use NLPipes on different tasks:

Name	Notebook	Description	Task	Size	Memory	Speed
GooglePlay Sentiment Detection	Available	Train a model to detect the sentiment polarity from the GooglePlay store	Single-label classification
StackOverflow tags Detection	Available	Train a model to detect tags from the StackOverFlow questions	Multiple-labels classification
GooglePlay Aspect and Sentiment Detection	Coming soon	Train a model to detect the aspects from GooglePlay store reviews along their assocated sentiment polarity	Aspect-based classification

Notices

• NLPipes is still in its early stage. The library comes with no warranty and future releases could bring substantial API and behavior changes.
• NLPipes will improve in the future releases, but the library is currently not optimized for high speed or low memory footprint.

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