Hugging Face

Hugging Face is a company developing social artificalartificial intelligence (AI)-run chatbot applications and natural language processing technologies (NLP) to facilitate AI-powered communication. The company's platform is capable of analyzing tone and word usage to decide what a chat may be about and enable the system to chat based on emotions. Hugging Face's platform allows users to build, train, and deploy NLP models with the intent of making the models more accessible to users.

Hugging Face is a company developing social artifical intelligenceartifical intelligence (AI)-run chatbot applications and natural language processingnatural language processing technologies (NLP) to facilitate AI-powered communication. The company's platform is capable of analyzing tone and word usage to decide what a chat may be about and enable the system to chat based on emotions. Hugging Face's platform allows users to build, train, and deploy NLP models with the intent of making the models more accessible to users.

Hugging Face's platform is developed to allow users to build, train, and deploy machine learningmachine learning (ML) and artificial intelligence models powered by open-source systems. This includes the following components:

The company’s main platform includes the company's chatbot applications, which allow users to interact with the artificial intelligence that the company developed. To accomplish this, Hugging Face developed its own natural language processing (NLP) model called Hierarchical Multi-Task Learning (HMTL) and managed a library of pre-trained NPL models under PyTorch-Transformers. Their chatbot applications are, as of September 2019, only available on iOS. These applications are Chatty, Talking Dog, Talking Egg, and Boloss. These AIs are intended to be a digital companioncompanions that can entertain users.

HuggingChat is an AI-powered, open-source chatbot built with 30 billion parameters and based on the latest LLaMa model developed by the project OpenAssistant. Considered a ChatGPT clone, HuggingChat is developed to be quick and straightforward and offer an open-source chatbot model available to anyone. Further, Hugging Face's goal with HuggingChat is to make the chatbot small and efficient so that it can be run on consumer hardware. Data privacy is strict on HuggingChat, which enforces a privacy model where messages are only stored to display them to the user and are not shared for research or training purposes, nor are users authenticated or identified using cookies.

Similar to the regular hub on Hugging Face's platform, the Private Hub allows users to experiment, collaborate, train, and develop ML models with a private group of collaborators, rather than a public group.

Hugging Face's AutoTrain solution offers a chance to automatically train, evaluate, and deploy ML models without needing to know how to code. The solution allows users to define the task they need the model to accomplish and upload the necessary data, and AutoTrain finds the best models for the data and task accomplishment and trains the model automatically.

Hugging Face and ServiceNow partnered to develop StarCoder, an open-source language model for code, offering a free AI code-generating system alternative to GitHub's Copilot, DeepMind's AlphaCode, and Amazon's CodeWhisperer. StarCoder was trained in over 80eighty programming languages and text from GitHub repositories, and trained on over 1 trillion tokens with a context window of 8192 tokens, to give the model 15.5 billion parameters.

HuggingChat is an AI-powered open-source chatbot built with 30 billion parameters and based on the latest LLaMa model developed by the project OpenAssistant. Considered a ChatGPT clone, HuggingChat is developed to be quick and straightforward and offer an open-source chatbot model available to anyone. Further, Hugging Face's goal with HuggingChat is to make the chatbot small and efficient so that it can be run on consumer hardware. Data privacy is strict on HuggingChat, which enforces a privacy model where messages are only stored to display them to the user and are not shared for research or training purposes, nor are users authenticated or identified using cookies.

Hugging Face and ServiceNow partnered to develop StarCoder, an open-source language model for code, offering a free AI code-generating system alternative to GitHub's Copilot, DeepMind's AlphaCode, and Amazon's CodeWhisperer. StarCoder was trained in over 80 programming languages and text from GitHub repositories, and trained on over 1 trillion tokens with a context window of 8192 tokens, to give the model 15.5 billion parameters.