Skip to content

Official extension for ASReview LAB enabling state-of-the-art NLP models with dense embeddings and deep learning architectures. Ideal for systematic reviews where lightweight models fall short.

License

Notifications You must be signed in to change notification settings

asreview/asreview-dory

Repository files navigation

ASReview Dory 🐟

DOI

ASReview Dory is an extension to the ASReview software, providing new models for classification and feature extraction. The extension is maintained by the ASReview LAB team.

Installation

You can install ASReview Dory via PyPI using the following command:

pip install asreview-dory

⚠️ XGBoost on MacOS If you are using macOS and plan to use XGBoost, you should first install OpenMP (brew install libomp)

Model components

Feature Extractors:

GTR T5
LaBSE
MPNet
Multilingual E5
MXBAI

Classifiers:

AdaBoost
Neural Network - 2-Layer
Neural Network - Dynamic
Neural Network - Warm Start
XGBoost

Explore the performance of these models in our Simulation Gallery! Look for the 🐟 icon to spot the Dory models.

Usage

Once installed, the plugins will be available in the front-end of ASReview, as well as being accessible via the command-line interface.

You can check all available models using:

asreview algorithms

Caching Models

You can pre-load models to avoid downloading them during runtime by using the cache command. To cache specific models, such as xgboost and sbert, run:

asreview dory cache nb xgboost sbert

To cache all available models at once, use:

asreview dory cache-all

Compatibility

This plugin is compatible with ASReview version 2 or later. Ensure that your ASReview installation is up-to-date to avoid compatibility issues.

The development of this plugin is done in parallel with the development of the ASReview software. We aim to maintain compatibility with the latest version of ASReview, but please report any issues you encounter.

Contributing

We welcome contributions from the community. To contribute, please follow these steps:

  1. Fork the repository.
  2. Create a new branch for your feature or bug fix.
  3. Implement your changes.
  4. Commit your changes with a clear message.
  5. Push your changes to your fork.
  6. Open a pull request to the main repository.

Please ensure your code adheres to the existing style and includes relevant tests.

For any questions or further assistance, feel free to contact the ASReview Lab Developers.


Enjoy using ASReview Dory! We hope these new models enhance your systematic review processes.

About

Official extension for ASReview LAB enabling state-of-the-art NLP models with dense embeddings and deep learning architectures. Ideal for systematic reviews where lightweight models fall short.

Topics

Resources

License

Code of conduct

Stars

Watchers

Forks

Sponsor this project

Packages

No packages published

Contributors 5

Languages