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Description
ExecuTorch is an open-source framework developed for PyTorch, specifically designed to deploy AI and machine learning models directly onto edge devices, facilitating tasks such as text, vision, speech, recommendation, and multimodal inference without the need for cloud connectivity. This framework allows for the exportation of models from PyTorch without any need for intermediate conversion formats, effectively maintaining ATen operators and employing ahead-of-time compilation to enhance performance tailored to specific hardware prior to deployment. Developers benefit from a modular architecture that offers flexibility in selecting both compile-time and runtime optimizations, all within the well-known PyTorch environment, which includes torchao specifically for quantization. With a lightweight C++ runtime that occupies roughly 50 KB, ExecuTorch is versatile enough to operate on a variety of platforms, including smartphones, desktops, embedded systems, microcontrollers, DSPs, and Cortex-M processors. It is compatible with multiple operating systems such as Android, iOS, Linux, Windows, macOS, and WebAssembly, and offers native APIs in C++, Swift, Kotlin, and Objective-C. As a result, ExecuTorch provides developers with a powerful tool to streamline the deployment of AI models across diverse devices and applications.
Description
The startup duration and memory usage of your application are independent of the codebase's size, leading to a significant improvement in startup speed, rapid processing capabilities, and a reduced memory usage. When utilizing reflection-driven IoC frameworks for application development, the framework retrieves and stores reflection information for each bean present in the application context. It also features integrated cloud functionalities, such as discovery services, distributed tracing, and support for cloud environments. You can swiftly configure your preferred data access layer and create APIs for custom implementations. Experience quick advantages by employing well-known annotations in familiar ways. Additionally, you can effortlessly set up servers and clients within your unit tests, allowing for immediate execution. This framework offers a straightforward, compile-time aspect-oriented programming interface that avoids reliance on reflection, enhancing efficiency and performance even further. As a result, developers can focus more on coding and optimizing their applications without the overhead of complex configurations.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
C++
Facebook
Google Cloud Platform
HashiCorp Consul
Instagram
IntelliJ IDEA
Kotlin
LLaVA
Llama 3.2
Integrations
Amazon Web Services (AWS)
C++
Facebook
Google Cloud Platform
HashiCorp Consul
Instagram
IntelliJ IDEA
Kotlin
LLaVA
Llama 3.2
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
ExecuTorch
Country
United States
Website
executorch.ai/
Vendor Details
Company Name
Micronaut Framework
Founded
2018
Country
United States
Website
micronaut.io