Hugging Face: Difference between revisions

Hugging face is a [[company]] that works on the field of [[artificial intelligence]] ([[AI]]), self-described as the “home of [[machine learning]].” <ref name="”1”">Romano, R (2022).  An introduction to Hugging Face transformers for NLP. Qwak. https://www.qwak.com/post/an-introduction-to-hugging-face-transformers-for-nlp</ref> It’s a community and data science platform that provides both tools that empower users to build, train, and deploy [[machine learning]] ([[ML]]) [[models]] that are based on [[open-source]] code, and a place where a community of researchers, data scientists, and ML engineers can participate by sharing ideas and contributing to open source projects. <ref name="”2”">Mahmood, O (2022). What’s Hugging Face? Towards Data Science. https://towardsdatascience.com/whats-hugging-face-122f4e7eb11a</ref> Its open-source hub offers a library of state-of-the-art models for [[Natural Language Processing]] ([[NLP]]), [[computer vision]], and others that are relevant to AI. In August 2022, there were more than 61 thousand [[pre-trained models]]. Technological giants like [[Microsoft]], [[Google]], [[Facebook]], [[Apple]], [[AWS]], and others have used Hugging Face’s models, datasets, and libraries. <ref name="”3”">Nabeel, M. What is Hugging Face? Educative. https://www.educative.io/answers/what-is-huggingface</ref> <ref name="”4”">Syal, A (2020). Hugging Face: A Step Towards Democratizing NLP. Towards Data Science. https://towardsdatascience.com/hugging-face-a-step-towards-democratizing-nlp-2c79f258c951</ref>