Company Profile

Hugging Face

Headquarters

New York, USA

Founded Year

2016

Website

Hugging Face

Operating Status

Active

Social Media

Founders

Clem Delangue
Co-Founder, CEO

Thomas Wolf
Co-Founder, CSO

Julien Chaumond
Co-Founder, CTO

About

In today's rapidly evolving tech landscape, few companies have managed to capture the attention of both researchers and industry professionals quite like Hugging Face. This dynamic company has carved out a unique niche by spearheading advancements in Natural Language Processing (NLP) and democratizing access to state-of-the-art machine learning models.

From the outset, Hugging Face recognized the transformative potential of NLP, specifically the power of pre-trained language models, in revolutionizing various applications across diverse sectors.

The model hub provides a comprehensive collection of pre-trained models that span a wide array of languages, tasks, and domains, enabling users to hit the ground running with their NLP applications.

Hugging Face has garnered immense support and collaboration from the AI community. Their open-source libraries, such as Transformers and Tokenizers, have gained significant traction, empowering developers to build and fine-tune NLP models with ease. Leveraging the power of this collaborative ecosystem, Hugging Face has cultivated an engaged and thriving community, driving innovation forward and fostering knowledge sharing.

At the heart of Hugging Face's success lies its vibrant and passionate community. The company has created a space for researchers and practitioners to collaborate, exchange ideas, and collectively push the boundaries of NLP. Through their community platform, users can engage in discussions, share insights, and contribute to the continuous improvement of models and tools. This community-centric approach not only fosters innovation but also creates a supportive environment that nurtures the growth of individuals and teams.

Hugging Face

Reinforcement Learning from Human Feedback From Zero to ChatGPT

In this talk, we will cover the basics of Reinforcement Learning from Human Feedback (RLHF) and how this technology is being used to enable state-of-the-art ML tools like ChatGPT. Most of the talk will be an overview of the interconnected ML models and cover the basics of Natural Language Processing and RL that one needs to understand how RLHF is used on large language models. It will conclude with open question in RLHF.

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