Skip to main content

A Sentiment Analysis Library for Research on top of PyTorch

Project description

TorchSenti

Sentiment Analysis Library for Research with PyTorch

TorchSenti provides sentiment analysis datasets from a simple one (positive/negative labels) to fine-grained one (aspect-based). TorchSenti is compatible with PyTorch to develop model and use pre-trained model to benchmark your work with other researchers.

Features

- Text Cleansing e.g removing hyperlinks
- WordPiece Tokenization with tagging for aspect extraction
- Entity metrics for aspect detection

Dataset Available

- **Sentiment Analysis**
    - IMDB Movie Reviews
    - Pros and Cons
    - Movie Review
    - Trip Advisor
    - City Search Data
    - Yelp Review
- **Aspect-based Sentiment Analysis**
    - SemEval 2014 Task 4 (ToDo)
    - SemEval 2015 Task 12 (ToDo)
    - SemEval 2016 Task 5 (ToDo)

Installation

You can install TorchSenti using pip

    pip install torchsenti

from source

    git clone https://github.com/jakartaresearch/pytorch-sentiment.git
    cd pytorch-sentiment
    python setup.py install

Getting Started

Contributors

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for torchsenti, version 0.0.8
Filename, size File type Python version Upload date Hashes
Filename, size torchsenti-0.0.8.tar.gz (8.6 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page