HUGGING FACE: A SCHOLARLY AND SCIENTIFIC ANALYSIS OF AI-ENHANCED OPEN-SOURCE NLP PLATFORMS

Abstract

Hugging Face is a leading artificial intelligence (AI)-driven platform that democratizes access to natural language processing (NLP) through open-source models, datasets, and tools, empowering over 4 million monthly active users to develop and deploy advanced language and multimodal AI applications. Anchored in transformer-based large language models (LLMs) and a robust ecosystem of over 2 million models and 500,000 datasets, Hugging Face facilitates tasks like text generation, sentiment analysis, and machine translation via its Transformers library and AutoML tools. Its enterprise-grade solutions, including Spaces and Inference Endpoints, support researchers, developers, and organizations in fields such as academia, healthcare, and technology, reducing development time by up to 70% while fostering collaborative innovation through open science principles.