made easy
See the full documentation for interactive quickstarts, step-by-step tutorials, and the complete API reference.
Build your efficient Neuro AI data loader.
pip install neuralsetFetch curated Neuro AI datasets.
pip install neuralfetchTrain Neuro AI models at scale.
pip install neuraltrainUnified benchmark for NeuroAI models.
pip install neuralbench- exca — Execution & caching framework powering neuroai's backbone
This project is licensed under the MIT License.
References to third-party content are subject to their own licenses.
If you use neuroai in your research, please cite NeuralSet: A High-Performing Python Package for Neuro-AI:
@article{king2026neuralset,
title = {NeuralSet: A High-Performing Python Package for Neuro-AI},
author = {King, J-R. and Bel, C. and Evanson, L. and Gadonneix, J. and Houhamdi, S. and L{\'e}vy, J. and Raugel, J. and Santos Revilla, A. and Zhang, M. and Bonnaire, J. and Caucheteux, C. and D{\'e}fossez, A. and Desbordes, T. and Diego-Sim{\'o}n, P. and Khanna, S. and Millet, J. and Orhan, P. and Panchavati, S. and Ratouchniak, A. and Thual, A. and Brooks, T. and Begany, K. and Benchetrit, Y. and Careil, M. and Banville, H. and d'Ascoli, S. and Dahan, S. and Rapin, J.},
year = {2026},
url = {https://kingjr.github.io/files/neuralset.pdf},
note = {Preprint; URL will be updated when the paper lands on arXiv}
}