LiteRTGoogle
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Related Products
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About
Flower is an open source federated learning framework designed to simplify the development and deployment of machine learning models across decentralized data sources. It enables training on data located on devices or servers without transferring the data itself, thereby enhancing privacy and reducing bandwidth usage. Flower supports a wide range of machine learning frameworks, including PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and XGBoost, and is compatible with various platforms and cloud services like AWS, GCP, and Azure. It offers flexibility through customizable strategies and supports both horizontal and vertical federated learning scenarios. Flower's architecture allows for scalable experiments, with the capability to handle workloads involving tens of millions of clients. It also provides built-in support for privacy-preserving techniques like differential privacy and secure aggregation.
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About
LiteRT (Lite Runtime), formerly known as TensorFlow Lite, is Google's high-performance runtime for on-device AI. It enables developers to deploy machine learning models across various platforms and microcontrollers. LiteRT supports models from TensorFlow, PyTorch, and JAX, converting them into the efficient FlatBuffers format (.tflite) for optimized on-device inference. Key features include low latency, enhanced privacy by processing data locally, reduced model and binary sizes, and efficient power consumption. The runtime offers SDKs in multiple languages such as Java/Kotlin, Swift, Objective-C, C++, and Python, facilitating integration into diverse applications. Hardware acceleration is achieved through delegates like GPU and iOS Core ML, improving performance on supported devices. LiteRT Next, currently in alpha, introduces a new set of APIs that streamline on-device hardware acceleration.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Machine learning practitioners and researchers in search of a tool to implement privacy-preserving, decentralized model training across diverse devices and platforms
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Audience
Mobile application developers in search of a tool to integrate efficient, on-device AI capabilities into their apps
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationFlower
Founded: 2023
Germany
flower.ai/
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Company InformationGoogle
Founded: 1998
United States
ai.google.dev/edge/litert
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Alternatives |
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Categories |
Categories |
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Integrations
JAX
PyTorch
Python
TensorFlow
Amazon Web Services (AWS)
Android
Apple iOS
C++
Docker
Google AI Edge Gallery
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Integrations
JAX
PyTorch
Python
TensorFlow
Amazon Web Services (AWS)
Android
Apple iOS
C++
Docker
Google AI Edge Gallery
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