What is the Transformers library?

The Transformers library is a collection of state-of-the-art AI models for PyTorch, providing pre-trained models for various NLP tasks.

What kind of hardware can I use with Spaces?

Spaces offers a variety of hardware options, including CPUs and GPUs like Nvidia T4, L4, L40S, A10G, A100, and H200.

Hugging Face

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Overview

Hugging Face is a leading collaboration platform for the machine learning community, offering tools and resources to build, share, and deploy AI models. It provides a central hub for accessing and hosting Git-based models, datasets, and Spaces. The platform’s open-source stack includes Transformers, Diffusers, and Accelerate, designed to optimize ML workflows. Hugging Face allows users to train and deploy models using Inference Endpoints and Spaces, which can be upgraded with custom on-demand hardware. The ecosystem supports diverse modalities like text, image, video, audio, and 3D, enabling users to build comprehensive ML portfolios. Enterprise solutions provide advanced security, access controls, and dedicated support, catering to teams building AI applications.

Common tasks

Model Training Inference Dataset Management Application Deployment

FAQ

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What is Hugging Face?

Hugging Face is a leading AI community and platform for building, sharing, and deploying machine learning models.

What are Inference Endpoints?

Inference Endpoints are a secure and scalable solution for deploying ML models directly from the Hugging Face Hub.

What is the Hugging Face Hub?

The Hugging Face Hub is a central repository for models, datasets, and applications, fostering collaboration and open-source development.

How do I deploy a model using Hugging Face?

You can deploy a model using Inference Endpoints, Spaces, or by integrating the model into an application using the Hugging Face API.

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