About us

tinyBIG is a website hosting the documentations, tutorials, examples and the latest updates about the tinybig library.

What is tinybig?

tinybig is a Python library developed by the IFM Lab for deep function learning model building.

• Official Website: https://www.tinybig.org/
• Github Repository: https://github.com/jwzhanggy/tinyBIG
• PyPI Package: https://pypi.org/project/tinybig/
• IFM Lab https://www.ifmlab.org/

Citing Us

tinybig is developed based on the RPN paper from IFM Lab, which can be downloaded via the following links:

• RPN 1 Paper (2024): https://arxiv.org/abs/2407.04819
• RPN 2 Paper (2024): https://arxiv.org/abs/2411.11162

If you find tinybig library and RPN papers useful in your work, please cite the RPN papers as follows:

@article{Zhang2024RPN_version1,
    title={RPN: Reconciled Polynomial Network Towards Unifying PGMs, Kernel SVMs, MLP and KAN},
    author={Jiawei Zhang},
    year={2024},
    eprint={2407.04819},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

@article{Zhang2024RPN_version2,
    title={RPN 2: On Interdependence Function Learning Towards Unifying and Advancing CNN, RNN, GNN, and Transformer},
    author={Jiawei Zhang},
    year={2024},
    eprint={2411.11162},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

Library Organization

Components	Descriptions
tinybig	a deep function learning library like torch.nn, deeply integrated with autograd
tinybig.model	a library providing the RPN models for addressing various deep function learning tasks
tinybig.module	a library providing the basic building modules for RPN model designing and implementation
tinybig.layer	a library providing the pre-defined rpn layers for rpn model designing
tinybig.head	a library providing the pre-defined rpn head for the rpn layer designing
tinybig.config	a library providing the configurations for model setups and instantiation
tinybig.expansion	a library providing the "data expansion functions" for effective data expansions
tinybig.compression	a library providing the "data compression functions" for effective data compressions
tinybig.transformation	a library providing the "data transformation functions" for effective data transformations
tinybig.reconciliation	a library providing the "parameter reconciliation functions" for parameter efficient learning
tinybig.remainder	a library providing the "remainder functions" for complementary information addition
tinybig.interdependence	a library providing the "interdependence functions" for interdependence relationships modeling
tinybig.fusion	a library providing the "fusion functions" for multi-source input fusion
tinybig.koala	a library providing the interdiciplinary methods and functions about other subjects and areas
tinybig.data	a library providing multi-modal datasets for solving various deep function learning tasks
tinybig.output	a library providing the processing method interfaces for output processing, saving and loading
tinybig.loss	a library providing the loss functions that can be used for RPN model learning
tinybig.metric	a library providing the metrics that can be used for RPN model performance evaluation
tinybig.optimizer	a library providing the optimizer that can be used for model optimization and learning
tinybig.learner	a library providing the learners that can be used for RPN model training and testing
tinybig.visual	a library of visualization functions for RPN model visualization and rendering
tinybig.util	a library of utility functions for RPN model design, implementation and learning
tinybig.zootopia	a library of the RPN model based diverse AI applications

License & Copyright

Copyright © 2024 IFM Lab. All rights reserved.

• tinybig source code is published under the terms of the MIT License.
• tinybig documentation and the RPN papers are licensed under a Creative Commons Attribution-Share Alike 4.0 Unported License (CC BY-SA 4.0).