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

    • Models

      Models. We’re on a journey to advance and democratize...

    • Datasets

      Datasets - Hugging Face – The AI community building the...

    • Log In

      Log In - Hugging Face – The AI community building the...

    • meta-llama/Llama-2-7b · Hugging Face

      CO 2 emissions during pretraining. Time: total GPU time...

    • Spaces

      Hugging Face. Models; Datasets; Spaces; Posts; Docs;...

    • Huggingchat

      The first open source alternative to ChatGPT. 💪. Making the...

    • Documentation

      Host Git-based models, datasets and Spaces on the Hugging...

    • Pricing

      Hugging Face Hub free. The HF Hub is the central place to...

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

  3. Hugging FaceThe AI community building the future. Create a new model. From the website. Hub documentation. Take a first look at the Hub features. Programmatic access. Use the Hub’s Python client library. Getting started with our git and git-lfs interface. You can create a repository from the CLI (skip if you created a repo from the website)

  4. www.hugging-face.org › modelsHuggingFace Models

    HuggingFace Models is a prominent platform in the machine learning community, providing an extensive library of pre-trained models for various natural language processing (NLP) tasks.

  5. en.wikipedia.org › wiki › Hugging_FaceHugging Face - Wikipedia

    Hugging Face, Inc. is a French-American company incorporated under the Delaware General Corporation Law and based in New York City that develops computation tools for building applications using machine learning.

  6. The AI community building the future. Hugging Face has 232 repositories available. Follow their code on GitHub.

  7. Nov 2, 2023 · Hugging Face AI is a platform and community dedicated to machine learning and data science, aiding users in constructing, deploying, and training ML models. It offers the necessary infrastructure for demonstrating, running, and implementing AI in real-world applications.

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