Company type | Private |
---|---|
Industry | Artificial intelligence, machine learning, software development |
Founded | 2016 |
Headquarters | |
Area served | Worldwide |
Key people |
|
Products | Models, datasets, spaces |
Revenue | 15,000,000 United States dollar (2022) |
Number of employees | 170 (2023) |
Website | huggingface |
Hugging Face, Inc. is a French-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.
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. [1] The company was named after the "hugging face" emoji. [1] 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. [2]
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. [3] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters. [4] [5]
In December 2022, the company acquired Gradio, an open source library built for developing machine learning applications in Python. [6]
On May 5, 2022, the company announced its Series C funding round led by Coatue and Sequoia. [7] 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. [8]
In February 2023, the company announced partnership with Amazon Web Services (AWS) which would allow Hugging Face's products 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. [9] [10] [11]
In August 2023, the company announced that it raised $235 million in a Series D funding, 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. [12]
The Transformers library is a Python package that contains open-source implementations of transformer models for text, image, and audio tasks. It is compatible with the PyTorch, TensorFlow and JAX deep learning libraries and includes implementations of notable models like BERT and GPT-2. [13] The library was originally called "pytorch-pretrained-bert" [14] which was then renamed to "pytorch-transformers" and finally "transformers."
The Hugging Face Hub is a platform (centralized web service) for hosting: [15]
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"), and machine learning demos ("Gradio"). [16]
Eclipse Deeplearning4j is a programming library written in Java for the Java virtual machine (JVM). It is a framework with wide support for deep learning algorithms. Deeplearning4j includes implementations of the restricted Boltzmann machine, deep belief net, deep autoencoder, stacked denoising autoencoder and recursive neural tensor network, word2vec, doc2vec, and GloVe. These algorithms all include distributed parallel versions that integrate with Apache Hadoop and Spark.
Annapurna Labs is an Israeli microelectronics company. Since January 2015 it has been a wholly-owned subsidiary of Amazon.com. Amazon reportedly acquired the company for its Amazon Web Services division for US$350–370M.
Feature engineering, a preprocessing step in supervised machine learning and statistical modeling, transforms raw data into a more effective set of inputs. Each input comprises several attributes, known as features. By providing models with relevant information, feature engineering significantly enhances their predictive accuracy and decision-making capability.
OpenAI is a U.S.-based artificial intelligence (AI) research organization founded in December 2015, researching artificial intelligence with the goal of developing "safe and beneficial" artificial general intelligence, which it defines as "highly autonomous systems that outperform humans at most economically valuable work". As one of the leading organizations of the AI spring, it has developed several large language models, advanced image generation models, and previously, released open-source models. Its release of ChatGPT has been credited with starting the AI spring.
The following table compares notable software frameworks, libraries and computer programs for deep learning.
Apache MXNet is an open-source deep learning software framework that trains and deploys deep neural networks. It aims to be scalable, allows fast model training, and supports a flexible programming model and multiple programming languages. The MXNet library is portable and can scale to multiple GPUs and machines. It was co-developed by Carlos Guestrin at the University of Washington, along with GraphLab.
spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. The library is published under the MIT license and its main developers are Matthew Honnibal and Ines Montani, the founders of the software company Explosion.
PyTorch is a machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella. It is recognized as one of the two most popular machine learning libraries alongside TensorFlow, offering free and open-source software released under the modified BSD license. Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface.
Amazon SageMaker is a cloud based machine-learning platform that allows the creation, training, and deployment by developers of machine-learning (ML) models on the cloud. It can be used to deploy ML models on embedded systems and edge-devices. SageMaker was launched in November 2017.
Generative Pre-trained Transformer 2 (GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained a dataset of 8 million web pages. It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019.
GitHub Copilot is a code completion tool developed by GitHub and OpenAI that assists users of Visual Studio Code, Visual Studio, Neovim, and JetBrains integrated development environments (IDEs) by autocompleting code. Currently available by subscription to individual developers and to businesses, the generative artificial intelligence software was first announced by GitHub on 29 June 2021, and works best for users coding in Python, JavaScript, TypeScript, Ruby, and Go. In March 2023 GitHub announced plans for "Copilot X", which will incorporate a chatbot based on GPT-4, as well as support for voice commands, into Copilot.
Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. It is considered to be a part of the ongoing AI boom.
deepset is an enterprise software vendor that provides developers with the tools to build production-ready natural language processing (NLP) systems. It was founded in 2018 in Berlin by Milos Rusic, Malte Pietsch, and Timo Möller. deepset authored and maintains the open source software Haystack and its commercial SaaS offering deepset Cloud.
GPT-J or GPT-J-6B is an open-source large language model (LLM) developed by EleutherAI in 2021. As the name suggests, it is a generative pre-trained transformer model designed to produce human-like text that continues from a prompt. The optional "6B" in the name refers to the fact that it has 6 billion parameters.
EleutherAI is a grass-roots non-profit artificial intelligence (AI) research group. The group, considered an open-source version of OpenAI, was formed in a Discord server in July 2020 to organize a replication of GPT-3. In early 2023, it formally incorporated as the EleutherAI Foundation, a non-profit research institute.
The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. It is composed of 22 smaller datasets, including 14 new ones.
LLaMA is a family of autoregressive large language models (LLMs), released by Meta AI starting in February 2023.
LangChain is a framework designed to simplify the creation of applications using large language models (LLMs). As a language model integration framework, LangChain's use-cases largely overlap with those of language models in general, including document analysis and summarization, chatbots, and code analysis.
Open-source artificial intelligence is the application of open-source practices to the development of artificial intelligence resources.
Whisper is a machine learning model for speech recognition and transcription, created by OpenAI and first released as open-source software in September 2022.