Hugging Face
Collaborate on unlimited models, datasets, and applications.
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Hugging Face Overview
Hugging Face is a collaboration platform for the machine learning community. - Offers advanced tools and solutions for building AI models. - Trusted by over 50,000 organizations including Meta, AWS, Google, and more. - Provides open-source tools like Transformers, Diffusers, and Safetensors for ML development.
Foundation Year
2016
Parent Company
Hugging Face
Founders
Clément Delangue Julien Chaumond Thomas Wolf
Application of Hugging Face
- Collaborate on unlimited models, datasets, and applications.
- Move faster with the HF Open source stack.
- Build your portfolio and share your work with the world.
- Accelerate your ML with paid Compute and Enterprise solutions.
Who Can Use It?
- Data Scientists
- Software Developers
- AI community
- Machine learning community
- ML tooling community
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Hugging Face Price Structure
Free Trial Available
Yes
Yearly Pricing Level 1
Forever Free - $0
Pricing Level 2
PRO - $9 - Monthly
Pricing Level 3
Enterprise Hub - $20 per user - Monthly
Other Details
API Access Available
Yes
Technical Requirements
- The website requires a stable internet connection for accessing models, datasets, and applications.
- Compatibility with web browsers such as Chrome, Firefox, Safari, and Edge is necessary for optimal performance.
- Users may need access to computational resources for deploying models on optimized Inference Endpoints or updating applications to a GPU.
- The platform supports Pytorch, TensorFlow, and JAX for state-of-the-art ML, requiring compatible software for model development.
- Access to the website may require a device with sufficient hardware capabilities to handle the computational demands of running ML models and datasets.
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Pros and Cons
Pros
- Collaboration platform for machine learning community
- Host and collaborate on unlimited models, datasets, and applications
- Move faster with the HF Open source stack
- Explore all modalities: text, image, video, audio, 3D
- Build and share ML portfolio with the world
- Accelerate ML with paid Compute and Enterprise solutions
- Deploy on optimized Inference Endpoints or GPU in a few clicks
- Advanced platform with enterprise-grade security and support
Cons
- Limited access to advanced features for free users.
- High cost for enterprise solutions and paid compute.
- Potential security risks with sharing work on a public platform.
- Limited support for non-text modalities like audio and 3D.
- Lack of detailed information on data privacy and protection measures.
- Dependency on external platforms like Amazon Web Services and Google for certain functionalities.
- Limited customization options for models and datasets.
- Potential challenges in integrating with existing AI systems and workflows.
Disclaimer:
This data is based on open sources for informational purposes only. For complete accuracy, please visit the actual website to validate the information.
Community
Hugging Face Community
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