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Welcome to iamai, a powerful and comprehensive AI toolkit that seamlessly integrates multimodal machine learning capabilities with advanced tools for cross-platform robot development!
🌍 This library is designed to provide developers with a unified solution for creating intelligent systems that span multiple modalities and operate across diverse platforms.
First of all, in the field of machine learning, we drew inspiration from
the excellent design of Hugging Face <https://huggingface.co>
\ ’s
transformers <https://github.com/huggingface/transformers>
for the
use of pre-trained models. We would like to express our gratitude to the
authors of Hugging Face and their open-source community.
Secondly, regarding the cross-platform robot framework, it is primarily
based on st <https://github.com/st1020>
\ ’s
alicebot <https://github.com/AliceBotProject/alicebot>
. We have made
numerous adaptations to make it compatible with machine learning. We
would like to thank the st and alicebot open-source communities for
their contributions.
To avoid any potential disputes or misunderstandings, we have listed the
licenses of the projects we have used and express our gratitude towards
them. Please see credits.pdf <./docs/_static/assets/credits.pdf>
__.
.. index-end
Cite This Software
.. code:: bibtex
@inproceedings{Hsiang_IamAI_A_Python_2023, author = {Hsiang, Nianian}, month = aug, pages = {1--10}, publisher = {Association for AICMUniversity}, title = {{IamAI: A Python Library for Artificial Intelligence and RobotFramework}}, url = {https://pub.aicmu.ac.cn}, year = {2023} }
MIT <https://github.com/retrofor/iamai/blob/master/COPYING>
©
2023-PRESENT Retro for Wut? <https://github.com/retrofor>
.
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