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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.

Citing Us

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

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

@article{Zhang2024RPN,
    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}
}

Library Organization

Components Descriptions
tinybig a deep function learning library like torch.nn, deeply integrated with autograd
tinybig.expansion a library providing the "data expansion functions" for multi-modal data effective expansions
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.module a library providing the basic building blocks for RPN model designing and implementation
tinybig.model a library providing the RPN models for addressing various deep function learning tasks
tinybig.config a library providing model component instantiation from textual configuration descriptions
tinybig.learner a library providing the learners that can be used for RPN model training and testing
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.metric a library providing the metrics that can be used for RPN model performance evaluation
tinybig.util a library of utility functions for RPN model design, implementation and learning

Copyright © 2024 IFM Lab. All rights reserved.

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