Hugging Face

Extracted Attributes

• Industry

  Artificial Intelligence and Machine Learning

• Headquarters

  Brooklyn, New York City, USA

• Core Software

  Transformers library

• Founding Date

  2016-01-01

• Employee Count

  170 people

• European Office

  34, Rue du Caire, Paris, France

• Model Inventory

  1,000,000+ checkpoints

Timeline

• Hugging Face, Inc. is founded, beginning its inception as a company focused on machine learning computation tools. (Source: Wikidata)

  2016-01-01

• Publication of a comprehensive tutorial by Prof. Ryan Ahmed highlighting Hugging Face as one of the most powerful platforms in AI for developers and researchers. (Source: Web Search Results)

  2025-09-24

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 allows users to share machine learning models and datasets and showcase their work.

Web Search Results

• Transformers

  Transformers acts as the model-definition framework for state-of-the-art machine learning models in text, computer. vision, audio, video, and multimodal model, for both inference and training. There are over 1M+ Transformers model checkpoints on the Hugging Face Hub you can use. Explore the Hub today to find a model and use Transformers to help you get started right away. Explore the Models Timeline to discover the latest text, vision, audio and multimodal model architectures in Transformers. Transformers provides everything you need for inference or training with state-of-the-art pretrained models. 1. Fast and easy to use: Every model is implemented from only three main classes (configuration, model, and preprocessor) and can be quickly used for inference or training with Pipeline or Trainer. If you’re new to Transformers or want to learn more about transformer models, we recommend starting with the LLM course. The course contains both theoretical and hands-on exercises to build a solid foundational knowledge of transformer models as you learn.

• Hugging Face – The AI community building the future.

  # The AI community building the future. The platform where the machine learning community collaborates on models, datasets, and applications. ## Models. #### Qwen/Qwen-Image-Edit-2511. #### Qwen/Qwen-Image-Layered. #### google/functiongemma-270m-it. #### Qwen Image Layered. Image edit, text to image, face swap, image upscale. #### Qwen Image Edit 2511. Host and collaborate on unlimited public models, datasets and applications. Share your work with the world and build your ML profile. ## Accelerate your ML. Give your team the most advanced platform to build AI with enterprise-grade security, access controls and. Access 45,000+ models from leading AI providers through a single, unified API with no service fees. #### Ai2. #### Google. We are building the foundation of ML tooling with the community. State-of-the-art AI models for PyTorch. State-of-the-art Diffusion models in PyTorch. Fast tokenizers optimized for research & production. Access & share datasets for any ML tasks. Serve language models with TGI optimized toolkit. Train PyTorch models with multi-GPU, TPU, mixed precision.

• Transformers: the model-definition framework for state ...

  🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. Transformers acts as the model-definition framework for state-of-the-art machine learning with text, computer vision, audio, video, and multimodal models, for both inference and training. from transformers import pipeline pipeline = pipeline task ="text-generation" model ="Qwen/Qwen2.5-1.5B" pipeline "the secret to baking a really good cake is " 'generated_text''the secret to baking a really good cake is 1) to use the right ingredients and 2) to follow the recipe exactly. from transformers import pipeline pipeline = pipeline task ="automatic-speech-recognition" model ="openai/whisper-large-v3" pipeline"https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/mlk.flac" 'text'' I have a dream that one day this nation will rise up and live out the true meaning of its creed.'. 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. audio python nlp machine-learning natural-language-processing deep-learning pytorch transformer speech-recognition glm pretrained-models hacktoberfest gemma vlm pytorch-transformers model-hub llm qwen deepseek.

• Hugging Face Tutorial for Beginners

  Hugging Face Tutorial for Beginners Prof. Ryan Ahmed 258000 subscribers 106 likes 10266 views 24 Sep 2025 This beginner-friendly tutorial walks you through the essentials of Hugging Face which is one of the most powerful platforms in AI and machine learning. You’ll learn: ✅ What Hugging Face is and why it matters ✅ How to explore pre-trained models on the Model Hub ✅ Running your first NLP tasks (text classification, sentiment analysis, translation, etc.) ✅ Using the transformers library to load and fine-tune models ✅ Practical tips for building real projects with Hugging Face Whether you’re a student, researcher, or developer, this tutorial gives you the foundation to start experimenting with state-of-the-art AI models today. 🔥Master LLM Engineering & AI Agents: https://www.udemy.com/course/become-an-llm-agentic-ai-engineer-14-day-bootcamp-2025/?couponCode=YOUTUBE_SEP 🚀Learn CoPilot and AI Agents: https://www.udemy.com/course/microsoft-copilot-365-ai-agents-for-business-bootcamp-2025/?couponCode=YOUTUBE_SEP 🎓Enroll in the Agentic AI Engineering Bootcamp: https://www.udemy.com/course/become-an-ai-agent-workflow-automation-engineer/?couponCode=AGENTICAI_YOUTUBE 🤖Master Generative AI and AI agents: https://www.udemy.com/course/generative-ai-chatgpt-copilot-agents-for-business-2025/?couponCode=YOUTUBE_SEP 👉Join our AI Community: https://www.skool.com/ai-made-simple-by-drryanahmed #huggingface #transformers #deeplearning #machinelearning #AI 2 comments

• Models – Hugging Face

  ### Edit Models filters. # Models. #### MiniMaxAI/MiniMax-M2.1. #### tencent/HY-MT1.5-1.8B. #### zai-org/GLM-4.7. #### Qwen/Qwen-Image-2512. #### LGAI-EXAONE/K-EXAONE-236B-A23B. #### tencent/WeDLM-8B-Instruct. #### Qwen/Qwen-Image-Edit-2511. #### lilylilith/AnyPose. #### tencent/HY-Motion-1.0. #### LiquidAI/LFM2-2.6B-Exp. #### fal/FLUX.2-dev-Turbo. #### ekwek/Soprano-80M. Text-to-Speech • 79.7M • Updated. #### unsloth/Qwen-Image-2512-GGUF. Text-to-Image • 20B • Updated. #### IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct. #### IQuestLab/IQuest-Coder-V1-40B-Instruct. #### Phr00t/Qwen-Image-Edit-Rapid-AIO. #### Qwen/Qwen-Image-Layered. Image-Text-to-Image • Updated. #### allura-forge/Llama-3.3-8B-Instruct. #### Tongyi-MAI/Z-Image-Turbo. #### inclusionAI/TwinFlow-Z-Image-Turbo. #### nvidia/NitroGen. #### google/functiongemma-270m-it. Text Generation • 0.3B • Updated. #### unsloth/Qwen-Image-Edit-2511-GGUF. Image-to-Image • 20B • Updated. #### upstage/Solar-Open-100B. #### unsloth/MiniMax-M2.1-GGUF. #### skt/A.X-K1. #### ResembleAI/chatterbox-turbo. #### lightx2v/Qwen-Image-Edit-2511-Lightning. #### naver-hyperclovax/HyperCLOVAX-SEED-Think-32B. #### microsoft/TRELLIS.2-4B. ## Run 15,000+ Models Instantly. Filter models and display only those with inference enabled via Inference Providers (Learn more).

• Country

  United States

• Employees

  170

• Instance Of

  Q210980

• Headquarters

  Brooklyn

• Inception Date

  1/1/2016