fastabx is a Python package for efficient computation of ABX discriminability.
The ABX discriminability is measures how well categories of interest are separated in the representation space by determining whether tokens from the same category are closer to each other than to those from a different category. While ABX has been mostly used to evaluate speech representations, it is a generic framework that can be applied to other domains of representation learning.
This package provides a simple interface that can be adapted to any ABX conditions, and to any input modality.
Check out the documentation for more information: https://docs.cognitive-ml.fr/fastabx
Install the pre-built package in your environment:
pip install fastabxIt requires Python 3.12 or later, and PyTorch 2.6.0 (CUDA 12.4 variant for Linux and Windows). Wheels are available for Linux x86-64 (glibc 2.34 or later), macOS 14 or later, and Windows x86-64.