LiteRT

LiteRT

Google
+
+

Related Products

  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • Fraud.net
    56 Ratings
    Visit Website
  • Qloo
    23 Ratings
    Visit Website
  • Source Defense
    7 Ratings
    Visit Website
  • SurveyJS
    64 Ratings
    Visit Website
  • RAD PDF
    3 Ratings
    Visit Website
  • Gaffa
    5 Ratings
    Visit Website
  • Highcharts
    123 Ratings
    Visit Website
  • cside
    37 Ratings
    Visit Website
  • Nutrient SDK
    111 Ratings
    Visit Website

About

Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API.

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.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers interested in an deep learning API solution to minimize the number of user actions required for common use cases

Audience

Mobile application developers in search of a tool to integrate efficient, on-device AI capabilities into their apps

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Pros & Cons from Real Users

Pros

  • I mostly code in Python, so using Keras for my deep learning needs wasn't too hard to get used to, given the abundance of documentation and ease of writing modular code with its API.

Cons

  • Keras only has high level APIs, unlike Tensorflow, which has both high and low level support.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Keras
United States
keras.io

Company Information

Google
Founded: 1998
United States
ai.google.dev/edge/litert

Alternatives

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Categories

Deep Learning Features

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Integrations

JAX
TensorFlow
BentoML
Comet
Dragonfly 3D World
GPUEater
Google AI Edge
Java
Jovian
Kotlin
ModelOp
Polyaxon
Python
RunCode
StreamFlux
Superwise
Unremot
teX.ai

Integrations

JAX
TensorFlow
BentoML
Comet
Dragonfly 3D World
GPUEater
Google AI Edge
Java
Jovian
Kotlin
ModelOp
Polyaxon
Python
RunCode
StreamFlux
Superwise
Unremot
teX.ai
Claim Keras and update features and information
Claim Keras and update features and information
Claim LiteRT and update features and information
Claim LiteRT and update features and information