Hugging Face

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Hugging Face is an American company that develops tools for building applications using machine learning. It is most notable for its transformers library built for natural language processing applications and its platform that allows users to share machine learning models and datasets. Hugging Face is a community and a platform for artificial intelligence and data science that aims to democratize AI knowledge and assets used in AI models. The platform allows users to build, train and deploy state of the art models powered by open source machine learning. It also provides a place where a broad community of data scientists, researchers, and ML engineers can come together and share ideas, get support and contribute to open source projects. Is there anything else you would like to know? - Wikipedia


Source: Conversation with Bing, 4/14/2023 (1) What is Hugging Face - A Beginner's Guide - ByteXD. https://bytexd.com/what-is-hugging-face-beginners-guide/. (2) Hugging Face – The AI community building the future.. https://huggingface.co/. (3) What's Hugging Face? An AI community for sharing ML models and datasets .... https://towardsdatascience.com/whats-hugging-face-122f4e7eb11a. (4) Private Hub - Hugging Face. https://huggingface.co/platform. (5) Hugging Face Hub documentation. https://huggingface.co/docs/hub/main. (6) What is Hugging Face - A Beginner's Guide - ByteXD. https://bytexd.com/what-is-hugging-face-beginners-guide/. allows users to share machine learning models and datasets.


Hugging Face NLP Library - Open Parallel Corpus (OPUS)

Hugging Face

OPUS is a growing collection of translated texts from the web. In the OPUS project we try to convert and align free online data, to add linguistic annotation, and to provide the community with a publicly available parallel corpus. OPUS is a project undertaken by the University of Helsinki and global partners to gather and open-source a wide variety of language data sets. OPUS is based on open source products and the corpus is also delivered as an open content package. We used several tools to compile the current collection. All pre-processing is done automatically. No manual corrections have been carried out. The OPUS collection is growing! ... OPUS the open parallel corpus