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Hugging Face

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This article is about the company. For the emoji, see Emoji.
Hugging Face, Inc.
Company typePrivate
IndustryArtificial intelligence
Machine learning
Software development
Founded2016; 9 years ago (2016)
Headquarters
Manhattan, New York City
Area served
Worldwide
Key people
  • Clément Delangue (CEO)
  • Julien Chaumond (CTO)
  • Thomas Wolf (CSO)
ProductsModels, datasets, spaces,
learn, inference, libraries
RevenueIncrease US$15 million (2022)
Number of employees
250[1] (2025)
Websitehuggingface.co

Hugging Face, Inc. is an American company based in New York City that develops computation 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 and showcase their work.

History

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The company was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf in New York City, originally as a company that developed a chatbot app targeted at teenagers.[2] The company was named after the U+1F917 🤗 HUGGING FACE emoji.[2] After open sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised US$40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5][6]

In December 2022, the company acquired Gradio, an open source library built for developing machine learning applications in Python.[7]

On May 5, 2022, the company announced its Series C funding round led by Coatue and Sequoia.[8] The company received a $2 billion valuation.

On August 3, 2022, the company announced the Private Hub, an enterprise version of its public Hugging Face Hub that supports SaaS or on-premises deployment.[9]

Clément Delangue in 2023

In February 2023, the company announced partnership with Amazon Web Services (AWS) which would allow Hugging Face's products to be available to AWS customers to use them as the building blocks for their custom applications. The company also said the next generation of BLOOM will be run on Trainium, a proprietary machine learning chip created by AWS.[10][11][12]

In August 2023, the company announced that it raised $235 million in a Series D funding round, at a $4.5 billion valuation. The funding was led by Salesforce and notable participation came from Google, Amazon, Nvidia, AMD, Intel, IBM, and Qualcomm.[13]

Thomas Wolf in 2024

In June 2024, the company announced, along with Meta and Scaleway, their launch of a new AI accelerator program for European startups. This initiative aims to help startups integrate open foundation models into their products, accelerating the EU AI ecosystem. The program, based at STATION F in Paris, will run from September 2024 to February 2025. Selected startups will receive mentoring, access to AI models and tools, and Scaleway’s computing power.[14]

On September 23, 2024, to further the International Decade of Indigenous Languages, Hugging Face teamed up with Meta and UNESCO to launch a new online language translator[15] built on Meta's No Language Left Behind open-source AI model, enabling free text translation across 200 languages, including many low-resource languages.[16]

On April 2025, Hugging Face announced that they acquired a humanoid robotics startup, Pollen Robotics. Pollen Robotics is a France based Robotics Startup founded by Matthieu Lapeyre and Pierre Rouanet in 2016.[17][18] In an X tweet, Clément Delangue, CEO of Hugging Face, shared his vision to make Artificial Intelligence robotics Open Source.[19]

Services and technologies

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Transformers Library

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The Transformers library is a Python package that contains open-source implementations of transformer models for text, image, and audio tasks. It is mainly compatible with the PyTorch library, but previous versions were also compatible with TensorFlow and JAX deep learning libraries. It includes implementations of notable models like BERT and GPT-2.[20] The library was originally called "pytorch-pretrained-bert"[21] which was then renamed to "pytorch-transformers" and finally "transformers."

A JavaScript version (Transformers.js[22]) has also been developed, allowing models to run directly in the browser through the ONNX runtime.

Hugging Face Hub

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The Hugging Face Hub is a platform (centralized web service) for hosting:[23]

  • Git-based code repositories, including discussions and pull requests for projects;
  • models, also with Git-based version control;
  • datasets, mainly in text, images, and audio;
  • web applications ("spaces"), intended for web-based/hosted demos of machine learning applications.

There are numerous pre-trained models that support common tasks in different modalities, such as:

  • Natural Language Processing: text classification, named entity recognition, question answering, language modeling, summarization, translation, multiple choice, and text generation.
  • Computer Vision: image classification, object detection, and segmentation.
  • Audio: automatic speech recognition and audio classification.

While in the past the Hub offered near-unlimited storage in both public and private repositories, they have since implemented storage quotas. For private storage, free users are limited to 100GB of data, while users with the Pro subscription ($9/month) can store up to 1TB of data. Public storage is limited to 5TB/10TB for Free and Pro users respectively.

Other libraries

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Gradio UI example

In addition to Transformers and the Hugging Face Hub, the Hugging Face ecosystem contains libraries for other tasks, such as dataset processing ("Datasets"), model evaluation ("Evaluate"), image generation ("Diffusers"), and machine learning demos ("Gradio").[24]

Safetensors

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The safetensors format was developed around 2021 to solve problems with the pickle format in Python. It was designed for saving and loading tensors. Compared to the pickle format, it allows lazy loading and avoids security problems.[25] After a security audit, it became the default format in 2023.[26]

The file format:

  • size of the header: 8 bytes, an unsigned little-endian 64-bit integer.
  • header: JSON UTF-8 string, formatted as {"TENSOR_NAME": {“dtype”: “F16”, “shape”: [1, 16, 256], “data_offsets”: [BEGIN, END]}, "NEXT_TENSOR_NAME": {…}, …}.
  • file: a byte buffer containing the tensors.

See also

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References

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  1. ^ Palazzolo, Stephanie (February 5, 2025). "Hugging Face Lays Off 4% of Staff". The Information.
  2. ^ a b "Hugging Face wants to become your artificial BFF". TechCrunch. March 9, 2017. Archived from the original on September 25, 2022. Retrieved September 17, 2023.
  3. ^ "Hugging Face raises $40 million for its natural language processing library". March 11, 2021. Archived from the original on July 28, 2023. Retrieved August 5, 2022.
  4. ^ "Inside BigScience, the quest to build a powerful open language model". VentureBeat. January 10, 2022. Archived from the original on July 1, 2022. Retrieved August 5, 2022.
  5. ^ "BLOOM". bigscience.huggingface.co. Archived from the original on November 14, 2022. Retrieved August 20, 2022.
  6. ^ "Inside a radical new project to democratize AI". MIT Technology Review. Archived from the original on December 4, 2022. Retrieved August 25, 2023.
  7. ^ Nataraj, Poornima (December 23, 2021). "Hugging Face Acquires Gradio, A Customizable UI Components Library For Python". Analytics India Magazine. Archived from the original on December 23, 2021. Retrieved January 26, 2024.
  8. ^ Cai, Kenrick. "The $2 Billion Emoji: Hugging Face Wants To Be Launchpad For A Machine Learning Revolution". Forbes. Archived from the original on November 3, 2022. Retrieved August 20, 2022.
  9. ^ "Introducing the Private Hub: A New Way to Build With Machine Learning". huggingface.co. Archived from the original on November 14, 2022. Retrieved August 20, 2022.
  10. ^ Bass, Dina (February 21, 2023). "Amazon's Cloud Unit Partners With Startup Hugging Face as AI Deals Heat Up". Bloomberg News. Archived from the original on May 22, 2023. Retrieved February 22, 2023.
  11. ^ Nellis, Stephen (February 21, 2023). "Amazon Web Services pairs with Hugging Face to target AI developers". Reuters. Archived from the original on May 30, 2023. Retrieved February 22, 2023.
  12. ^ "AWS and Hugging Face collaborate to make generative AI more accessible and cost efficient | AWS Machine Learning Blog". aws.amazon.com. February 21, 2023. Archived from the original on August 25, 2023. Retrieved August 25, 2023.
  13. ^ Leswing, Kif (August 24, 2023). "Google, Amazon, Nvidia and other tech giants invest in AI startup Hugging Face, sending its valuation to $4.5 billion". CNBC. Archived from the original on August 24, 2023. Retrieved August 24, 2023.
  14. ^ "META Collaboration Launches AI Accelerator for European Startups". Yahoo Finance. June 25, 2024. Archived from the original on July 11, 2024. Retrieved July 11, 2024.
  15. ^ "Hugging Face Spaces Translator". September 23, 2024.
  16. ^ "UNESCO Translator Event". September 23, 2024.
  17. ^ Wiggers, Kyle (April 14, 2025). "Hugging Face buys a humanoid robotics startup". TechCrunch. Retrieved April 15, 2025.
  18. ^ Koetsier, John. "Open Source Humanoid Robots That You Can 3D Print Yourself: Hugging Face Buys Pollen Robotics". Forbes. Retrieved April 15, 2025.
  19. ^ Knight, Will. "An Open Source Pioneer Wants to Unleash Open Source AI Robots". Wired. ISSN 1059-1028. Retrieved April 15, 2025.
  20. ^ "🤗 Transformers". huggingface.co. Archived from the original on September 27, 2023. Retrieved August 20, 2022.
  21. ^ "First release". GitHub. November 17, 2018. Archived from the original on April 30, 2023. Retrieved March 28, 2023.
  22. ^ "huggingface/transformers.js". GitHub. Archived from the original on March 7, 2023. Retrieved June 18, 2025.
  23. ^ "Hugging Face Hub documentation". huggingface.co. Archived from the original on September 20, 2023. Retrieved August 20, 2022.
  24. ^ "Hugging Face - Documentation". huggingface.co. Archived from the original on September 30, 2023. Retrieved February 18, 2023.
  25. ^ huggingface/safetensors, Hugging Face, September 21, 2024, retrieved September 22, 2024
  26. ^ "🐶Safetensors audited as really safe and becoming the default". huggingface.co. Retrieved September 22, 2024.
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