💵 What is it?

Index Compression Methods (INCOME) repository helps you easily train and evaluate memory-compressed binary retrievers on any custom dataset. We provide recent state-of-the-art techniques for training and unsupervised (without requiring custom training data) for domain-adaptation of NLP-based binary retrieval models across any dataset.

For more information, checkout our publication:

💵 Installation

One can either install income via pip

pip install income

or via source using git clone

$ git clone https://github.com/Nthakur20/income.git
$ cd income
$ pip install -e .

💵 Models Supported

Uploaded Public Models

💵 Quick Example

💵 Why should we do domain adaptation?

💵 Inference

💵 Training

💵 Citing & Authors

If you find this repository helpful, feel free to cite our recent publication: Domain Adaptation for Memory-Efficient Dense Retrieval:

  title={Domain Adaptation for Memory-Efficient Dense Retrieval},
  author={Thakur, Nandan and Reimers, Nils and Lin, Jimmy},
  journal={arXiv preprint arXiv:2205.11498},

The main contributors of this repository are:

Contact person: Nandan Thakur, [email protected]

Don’t hesitate to send us an e-mail or report an issue, if something is broken (and it shouldn’t be) or if you have further questions.

This repository contains experimental software and is published for the sole purpose of giving additional background details on the respective publication.


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