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    Hugging Face

    AI Solution

    We’re on a journey to advance and democratize artificial intelligence through open source and open science.

    Hugging Face Models Datasets Spaces Docs Solutions Pricing Log In Sign Up NEW HuggingChat Making the community's best AI chat models available to everyone. Start chatting The AI community building the future. Build, train and deploy state of the art models powered by the reference open source in machine learning. Star 98,789 More than 5,000 organizations are using Hugging Face Allen Institute for AI Non-Profit • 154 models Meta AI Company • 673 models Amazon Web Services Company • 1 model Google AI Company • 587 models Intel Company • 103 models SpeechBrain Non-Profit • 69 models Microsoft Company • 250 models Grammarly Company • 1 model Hub Home of Machine Learning Create, discover and collaborate on ML better. Join the community to start your ML journey. Sign Up Tasks Problems solvers Thousands of creators work as a community to solve Audio, Vision, and Language with AI. Explore tasks Image Classification 3,653 models Object Detection 395 models Question Answering 4,680 models Summarization 1,082 models Text Classification 21,815 models Translation 2,070 models Open Source Transformers Transformers is our natural language processing library and our hub is now open to all ML models, with support from libraries like Flair, Asteroid, ESPnet, Pyannote, and more to come. Read documentation huggingface@transformers:~ from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased') model = AutoModelForMaskedLM.from_pretrained('bert-base-uncased') On demand Inference API Serve your models directly from Hugging Face infrastructure and run large scale NLP models in milliseconds with just a few lines of code. Learn more distilbert-base-uncased Fill-Mask Examples Mask token: [MASK] The goal of life is [MASK]. Compute Computation time on Intel Xeon 3rd Gen Scalable cpu: 0.013 s happiness 0.036 survival 0.031 salvation 0.017 freedom 0.017 unity 0.015 JSON Output Maximize dbmdz/bert-large-cased-finetuned-conll03-english Token Classification Examples My name is Clara and I live in Berkeley, California. I work at this cool company called Hugging Face. Compute Computation time on Intel Xeon 3rd Gen Scalable cpu: 0.114 s My name is ClaraPER and I live in BerkeleyLOC, CaliforniaLOC. I work at this cool company called Hugging FaceORG. JSON Output Maximize Science Our Research contributions We're on a journey to advance and democratize NLP for everyone. Along the way, we contribute to the development of technology for the better. 🌸 T0 Multitask Prompted Training Enables Zero-Shot Task Generalization Open source state-of-the-art zero-shot language model out of BigScience. Read more 🐎 DistilBERT DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter A smaller, faster, lighter, cheaper version of BERT obtained via model distillation. Read more 📚 HMTL Hierarchical Multi-Task Learning Learning embeddings from semantic tasks for multi-task learning. We have open-sourced code and a demo. Read more 🐸 Dynamical Language Models Meta-learning for language modeling A meta learner is trained via gradient descent to continuously and dynamically update language model weights. Read more 🤖 State of the art Neuralcoref Our open source coreference resolution library for coreference. You can train it on your own dataset and language. Read more 🦄 Auto-complete your thoughts Write with Transformers This web app is the official demo of the Transformers repository's text generation capabilities. Start writing Website Model Hub Inference API AutoTrain Organizations Contributors Expert Acceleration Program Company About HF Store Brand assets Terms of service Privacy Jobs Press Resources Course Transformers docs Blog Forum Newsletter Service Status Social GitHub Twitter LinkedIn Discord

    About Hugging Face

    Hugging Face is an AI company that aims to democratize artificial intelligence through open source and open science. The company provides a range of products and services that enable users to build, train, and deploy state-of-the-art models powered by the reference open source in machine learning. Hugging Face's products include Models, Datasets, Spaces, Docs, and Solutions, which are designed to help users solve Audio, Vision, and Language problems with AI.

    Hugging Face's target market includes individuals, organizations, and companies that are interested in building and deploying AI models. The company has more than 5,000 organizations using its products, including the Allen Institute for AI, Meta AI, Amazon Web Services, Google AI, Intel, SpeechBrain, Microsoft, and Grammarly.

    Hugging Face's main use cases include Image Classification, Object Detection, Question Answering, Summarization, Text Classification, and Translation. The company's open-source Transformers library is its natural language processing library, and its hub is now open to all ML models, with support from libraries like Flair, Asteroid, ESPnet, Pyannote, and more to come. Hugging Face also offers an Inference API that enables users to serve their models directly from Hugging Face infrastructure and run large-scale NLP models in milliseconds with just a few lines of code.

    Hugging Face's mission is to advance and democratize NLP for everyone. The company contributes to the development of technology for the better and has made several research contributions, including Multitask Prompted Training Enables Zero-Shot Task Generalization, DistilBERT, a distilled version of BERT, Hierarchical Multi-Task Learning, Meta-learning for language modeling, Neuralcoref, and Auto-complete your thoughts.

    Hugging Face's website provides a range of resources, including a Model Hub, Inference API, AutoTrain, Organizations, Contributors, Expert Acceleration Program, and a Course. The company also offers brand assets, terms of service, privacy policy, job opportunities, press releases, and a blog. Hugging Face's social media presence includes GitHub, Twitter, LinkedIn, and Discord.

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