@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://preview.aclanthology.org/fix-sig-urls/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."
}