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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

Transformers is a versatile library that includes pretrained models for natural language processing, computer vision, audio, and multimodal tasks, facilitating both inference and training. With the Transformers library, you can effectively train models tailored to your specific data, create inference applications, and utilize large language models for text generation. Visit the Hugging Face Hub now to discover a suitable model and leverage Transformers to kickstart your projects immediately. This library provides a streamlined and efficient inference class that caters to various machine learning tasks, including text generation, image segmentation, automatic speech recognition, and document question answering, among others. Additionally, it features a robust trainer that incorporates advanced capabilities like mixed precision, torch.compile, and FlashAttention, making it ideal for both training and distributed training of PyTorch models. The library ensures rapid text generation through large language models and vision-language models, and each model is constructed from three fundamental classes (configuration, model, and preprocessor), allowing for quick deployment in either inference or training scenarios. Overall, Transformers empowers users with the tools needed to create sophisticated machine learning solutions with ease and efficiency.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

PyTorch
C++
Facebook
Hugging Face
Instagram
Kotlin
LLaVA
Llama 3.2
Objective-C
OpenAI Whisper
Phi-4-mini-reasoning
Qwen3
Swift
Voxtral
WhatsApp

Integrations

PyTorch
C++
Facebook
Hugging Face
Instagram
Kotlin
LLaVA
Llama 3.2
Objective-C
OpenAI Whisper
Phi-4-mini-reasoning
Qwen3
Swift
Voxtral
WhatsApp

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$9 per month
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

Hugging Face

Founded

2016

Country

United States

Website

huggingface.co/docs/transformers/en/index

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