Keepsake

Keepsake

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About

ExecuTorch is PyTorch’s open source framework for deploying AI/ML models directly to edge devices, enabling text, vision, speech, recommendation, and multimodal inference without requiring the cloud. It exports models from PyTorch without intermediate conversion formats, preserves ATen operators, and uses ahead-of-time compilation to optimize performance for target hardware before deployment. Its modular design lets developers choose compile-time and runtime optimizations while staying inside the familiar PyTorch ecosystem, including torchao for quantization. A portable C++ runtime with a base footprint of about 50 KB can run on smartphones, desktops, embedded systems, microcontrollers, DSPs, and Cortex-M processors. ExecuTorch supports Android, iOS, Linux, Windows, macOS, and WebAssembly, with native APIs for C++, Swift, Kotlin, and Objective-C.

About

Keepsake is an open-source Python library designed to provide version control for machine learning experiments and models. It enables users to automatically track code, hyperparameters, training data, model weights, metrics, and Python dependencies, ensuring that all aspects of the machine learning workflow are recorded and reproducible. Keepsake integrates seamlessly with existing workflows by requiring minimal code additions, allowing users to continue training as usual while Keepsake saves code and weights to Amazon S3 or Google Cloud Storage. This facilitates the retrieval of code and weights from any checkpoint, aiding in re-training or model deployment. Keepsake supports various machine learning frameworks, including TensorFlow, PyTorch, scikit-learn, and XGBoost, by saving files and dictionaries in a straightforward manner. It also offers features such as experiment comparison, enabling users to analyze differences in parameters, metrics, and dependencies across experiments.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI developers and engineering teams that need to deploy optimized PyTorch models for on-device inference across smartphones, embedded systems, and microcontrollers

Audience

Developers in need of a tool to manage their code and enhance the efficiency of their workflows

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version Supported
Free Trial Not Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

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

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

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

ExecuTorch
United States
executorch.ai/

Company Information

Replicate
United States
keepsake.ai/

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services

Alternatives

TensorBoard

TensorBoard

Tensorflow
LiteRT

LiteRT

Google

Categories

AI Inference Supported

Categories

Integrations

PyTorch Supported
Amazon S3 Not Supported
C++ Supported
Facebook Supported
Google Cloud Storage Not Supported
Instagram Supported
JSON Not Supported
Kotlin Supported
LLaVA Supported
Llama 3.2 Supported
Muse Glimmer Supported
Objective-C Supported
Phi-4-mini-reasoning Supported
Python Not Supported
Qwen3 Supported
Swift Supported
TensorFlow Not Supported
Voxtral Supported
WhatsApp Supported
scikit-learn Not Supported

Integrations

PyTorch Supported
Amazon S3 Supported
C++ Not Supported
Facebook Not Supported
Google Cloud Storage Supported
Instagram Not Supported
JSON Supported
Kotlin Not Supported
LLaVA Not Supported
Llama 3.2 Not Supported
Muse Glimmer Not Supported
Objective-C Not Supported
Phi-4-mini-reasoning Not Supported
Python Supported
Qwen3 Not Supported
Swift Not Supported
TensorFlow Supported
Voxtral Not Supported
WhatsApp Not Supported
scikit-learn Supported
Claim ExecuTorch and update features and information
Claim ExecuTorch and update features and information
Claim Keepsake and update features and information
Claim Keepsake and update features and information