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
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Edge AI developers who need to deploy PyTorch models efficiently across mobile, embedded, desktop, and specialized hardware

Audience

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

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

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

ExecuTorch
United States
executorch.ai/

Company Information

Replicate
United States
keepsake.ai/

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services

Alternatives

LiteRT

LiteRT

Google
TensorBoard

TensorBoard

Tensorflow

Categories

Categories

Integrations

PyTorch
Amazon S3
C++
Facebook
Google Cloud Storage
Instagram
JSON
Kotlin
LLaVA
Llama 3.2
Muse Glimmer
Objective-C
Phi-4-mini-reasoning
Python
Qwen3
Swift
TensorFlow
Voxtral
WhatsApp
scikit-learn

Integrations

PyTorch
Amazon S3
C++
Facebook
Google Cloud Storage
Instagram
JSON
Kotlin
LLaVA
Llama 3.2
Muse Glimmer
Objective-C
Phi-4-mini-reasoning
Python
Qwen3
Swift
TensorFlow
Voxtral
WhatsApp
scikit-learn
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