Hugging Face
Hugging Face is a collaborative AI platform and community focused on building the future of machine learning by sharing models, datasets, and applications. It offers tools, open-source libraries, and enterprise solutions to accelerate AI development.
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Free from Starting at $0.60/hour for GPU
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Hugging Face
Hugging Face is a platform where the machine learning community collaborates on models, datasets, and applications. It serves as a hub for creating, discovering, and sharing machine learning resources across various modalities including text, image, video, audio, and 3D. The platform supports both open-source projects and enterprise-grade solutions, enabling users to build, deploy, and scale AI models efficiently. With a large community and over 1 million models available, Hugging Face fosters innovation and accelerates AI development for researchers, developers, and organizations.
An open-source AI community and platform advancing and democratizing artificial intelligence through open source and open science, offering a vast repository of pre-trained models and datasets.
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Claim this listingKey Features
Model Hub
Access and share over 1 million pre-trained machine learning models across various tasks and modalities.
Datasets
Browse and contribute to a large collection of over 250,000 datasets for diverse machine learning applications.
Spaces
Host and explore thousands of AI applications and demos built by the community.
Open Source Libraries
Utilize state-of-the-art open-source libraries such as Transformers, Diffusers, Tokenizers, and more for ML development.
Compute and Inference Endpoints
Deploy models on optimized inference endpoints or upgrade Spaces applications with GPU support for scalable compute.
Enterprise Solutions
Enterprise-grade platform with security, access controls, single sign-on, audit logs, and dedicated support.
Community Collaboration
Engage with a vibrant community through forums, blogs, and shared projects to accelerate AI innovation.
Pricing
Free access to public models, datasets, Spaces, and open-source libraries with community support.
Compute
Starting at $0.60/hour for GPU- Optimized inference endpoints
- GPU upgrade for Spaces applications
Enterprise
Starting at $20/user/month- Enterprise-grade security
- Single Sign-On
- Priority support
- Audit logs
Use Cases
Model Sharing and Discovery
Researchers and developers can share pre-trained models and discover models for various AI tasks.
Dataset Management
Access and contribute to a wide range of datasets to support machine learning experiments and applications.
AI Application Hosting
Deploy and showcase AI-powered applications and demos using Hugging Face Spaces.
Enterprise AI Development
Organizations can leverage enterprise features for secure, scalable AI model development and deployment.
Open Source ML Tooling
Use and contribute to foundational open-source ML libraries for research and production.
Integrations
Inference Endpoints
Seamless deployment of models for real-time inference.
Open Source Libraries
Integration with popular ML frameworks like PyTorch, TensorFlow, and JAX through libraries such as Transformers and Diffusers.
Benefits
Limitations
Frequently Asked Questions
Can I use Hugging Face for free?
What enterprise features does Hugging Face provide?
How do I deploy a model on Hugging Face?
Does Hugging Face support multiple AI modalities?
Getting Started
- 1 Step 1: Sign up for a free account on the Hugging Face website.
- 2 Step 2: Explore models, datasets, and Spaces to find resources relevant to your project.
- 3 Step 3: Use open-source libraries or deploy models via inference endpoints or Spaces.
- 4 Step 4: For enterprise users, contact sales or visit the enterprise page to set up team access and security features.
Support
Contact [email protected] for press inquiries.
Documentation
Comprehensive docs available at https://www.huggingface.co/docs
Forum
Community support and discussions at https://discuss.huggingface.co/
Status
Service status updates at https://status.huggingface.co/
Social
Engage via GitHub, Twitter, LinkedIn, Discord, Zhihu, and WeChat.
API
API documentation is available at https://www.huggingface.co/docs
Rate limit information is not explicitly provided in the source content.
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