{"id":181782,"date":"2026-02-18T10:22:19","date_gmt":"2026-02-18T09:22:19","guid":{"rendered":"https:\/\/liora.io\/en\/?p=181782"},"modified":"2026-02-18T10:22:19","modified_gmt":"2026-02-18T09:22:19","slug":"all-about-hugging-face-%f0%9f%a4%97","status":"publish","type":"post","link":"https:\/\/liora.io\/en\/all-about-hugging-face-%f0%9f%a4%97","title":{"rendered":"Hugging Face ?: A Comprehensive Guide"},"content":{"rendered":"

Hugging Face is a company providing open source libraries containing pre-trained models. Specializing in machine learning, Hugging Face has developed its business with several innovative AI-based products. Today, the company aims to become the “GitHub of machine learning”.<\/strong><\/p>\n

What is Hugging Face?<\/h2>\nHugging Face<\/strong> is a French startup founded in 2015 by Julien Chaumond and Cl\u00e9ment Delangue. Their goal: to make artificial intelligence<\/a> accessible to everyone.\n\nTo achieve this, Hugging Face<\/strong> offers an open-source NLP (Natural language Processing) library.<\/a> In other words, they offer their customers an API facilitating access to pre-trained models.\n\nAs these machine learning<\/a> models are already trained, their learning and experimentation are simplified. As a bonus, they also offer tools for managing existing data and models, and for developing and training new models.\n\nSince its launch, the company has experienced exponential growth and is well on its way to becoming one of the benchmarks in the artificial intelligence sector. In 2020, it was named one of the world’s most innovative companies by MIT Technology Review.<\/strong>\n

What are Hugging Face’s solutions?<\/h2>
\"steps-financing-startup-pre-seed-series-c.jpg\"<\/figure>\nOver the years, Hugging Face<\/strong>\n

The Transformers library<\/h3>\nTo help its community manage and develop its Machine Learning<\/a> models, Hugging Face<\/strong> offers several open source libraries. The best known is Transformers, a library designed to train and deploy Python-based NLP models<\/a>. They can then perform a variety of natural language processing tasks, such as classification, text generation, named entity detection, information extraction, question answering…<\/strong>\n\nTo perform all these tasks, Tranformers uses inference training.\n\nTraining is the traditional method used in machine learning<\/a>. By simply presenting labeled data, the model is gradually trained. As it trains, its performance increases.\nInference, on the other hand, enables much more advanced models to be designed, as they train on unlabeled information. Each model will learn by itself (always on the basis of references learned beforehand).\n

Other libraries<\/h3>\nIn addition to Transformers, Hugging Face<\/strong> also offers its Datasets library, providing access to over 100 NLP datasets. Or Tokenizers, which tokenizes over 40 languages.\n\nGood to know<\/strong>: Hugging Face also offers NLP training.<\/a> Users can then take advantage of all these available libraries.\n\n\nTraining in Data Science\n<\/a>\n

Accelerate<\/h4>\nIt’s an API that lets developers and data scientists run their own scripts and code their own training loops. And all this in different types of configuration.\n\nAnd to make learning NLP easier<\/a>, Hugging Face also offers users a CLI tool for quickly configuring and testing training environments.\n

Spaces<\/h4>\nAs Hugging Face<\/strong> has developed a genuine community strategy, it also offers model hosting. More precisely, an exchange zone where community members share their Machine Learning applications.\n\nThey can then create their apps directly with Hugging Face<\/strong>. And thanks to version control, collaboration is simplified to design even more powerful and innovative ML models<\/a>.\n

Les chatbots<\/h3>\nHugging Face first made a name for itself through its chatbot applications. It’s worth mentioning them, even if they’re no longer their core business. These were developed using the company’s natural language processing model (Hierarchical Multi-Task Learning – HMTL).<\/strong>\n\nAvailable applications include Chatty>, Talking Dog, Talking Egg and Boloss.\n\nInitially, these were mainly chatbots<\/a> for teenagers. But gradually, Hugging Face developed into a reference in the field of Machine Learning.\n\n

What does the future hold for Hugging Face?<\/h2>
\"training-screen-ai-transformers-model.jpg\"<\/figure>\nHugging<\/strong> may have started out as a simple chatbot for teenagers, but today their ambition goes much further.\n\nAnd with good reason:<\/strong> since their creation, they’ve been multiplying their fundraising efforts.\n