Hugging Face helps you quickly and efficiently deploy state-of-the-art machine learning models for natural language processing projects.
Hugging Face is an open-source provider of NLP technologies. According to the website, it offers a library of ML models with support from libraries like Flair, Asteroid, ESPnet, and Pyannote. Users can serve models directly from Hugging Face infrastructure and run large scale NLP models in milliseconds. It also features a zero-shot language model out of BigScience, as well as a smaller, faster, lighter, and cheaper version of BERT, and an open source coreference resolution library.
Data Scientists can use Hugging Face to quickly and efficiently deploy state-of-the-art machine learning models, while Natural Language Processing Engineers can use it to collaborate on ML projects. AI Researchers can use it to access open source language models and train embeddings from semantic tasks. Hugging Face differentiates itself from similar competitors with its comprehensive open-source NLP technology suite and wide range of ML libraries.
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