@inproceedings{sharma-etal-2024-aixplain-sdk,
title = "ai{X}plain {SDK}: A High-Level and Standardized Toolkit for {AI} Assets",
author = "Sharma, Shreyas and
Pavanelli, Lucas and
Castro Ferreira, Thiago and
Al-Badrashiny, Mohamed and
Sawaf, Hassan",
editor = "Mahamood, Saad and
Minh, Nguyen Le and
Ippolito, Daphne",
booktitle = "Proceedings of the 17th International Natural Language Generation Conference",
month = sep,
year = "2024",
address = "Tokyo, Japan",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.inlg-main.37",
pages = "446--452",
abstract = "The aiXplain SDK is an open-source Python toolkit which aims to simplify the wide and complex ecosystem of AI resources. The toolkit enables access to a wide selection of AI assets, including datasets, models, and metrics, from both academic and commercial sources, which can be selected, executed and evaluated in one place through different services in a standardized format with consistent documentation provided. The study showcases the potential of the proposed toolkit with different code examples and by using it on a user journey where state-of-the-art Large Language Models are fine-tuned on instruction prompt datasets, outperforming their base versions.",
}
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<abstract>The aiXplain SDK is an open-source Python toolkit which aims to simplify the wide and complex ecosystem of AI resources. The toolkit enables access to a wide selection of AI assets, including datasets, models, and metrics, from both academic and commercial sources, which can be selected, executed and evaluated in one place through different services in a standardized format with consistent documentation provided. The study showcases the potential of the proposed toolkit with different code examples and by using it on a user journey where state-of-the-art Large Language Models are fine-tuned on instruction prompt datasets, outperforming their base versions.</abstract>
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%0 Conference Proceedings
%T aiXplain SDK: A High-Level and Standardized Toolkit for AI Assets
%A Sharma, Shreyas
%A Pavanelli, Lucas
%A Castro Ferreira, Thiago
%A Al-Badrashiny, Mohamed
%A Sawaf, Hassan
%Y Mahamood, Saad
%Y Minh, Nguyen Le
%Y Ippolito, Daphne
%S Proceedings of the 17th International Natural Language Generation Conference
%D 2024
%8 September
%I Association for Computational Linguistics
%C Tokyo, Japan
%F sharma-etal-2024-aixplain-sdk
%X The aiXplain SDK is an open-source Python toolkit which aims to simplify the wide and complex ecosystem of AI resources. The toolkit enables access to a wide selection of AI assets, including datasets, models, and metrics, from both academic and commercial sources, which can be selected, executed and evaluated in one place through different services in a standardized format with consistent documentation provided. The study showcases the potential of the proposed toolkit with different code examples and by using it on a user journey where state-of-the-art Large Language Models are fine-tuned on instruction prompt datasets, outperforming their base versions.
%U https://aclanthology.org/2024.inlg-main.37
%P 446-452
Markdown (Informal)
[aiXplain SDK: A High-Level and Standardized Toolkit for AI Assets](https://aclanthology.org/2024.inlg-main.37) (Sharma et al., INLG 2024)
ACL