Keepsake vs. PyTorch Comparison


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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.	About Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.
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	Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Not Supported On-Premises Not Supported iPhone Supported iPad Supported Android Supported Chromebook Not Supported
Audience Developers in need of a tool to manage their code and enhance the efficiency of their workflows	Audience Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment
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 Not Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing Free Free Version Supported Free Trial Not Supported	Pricing No information available. Free Version Not 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 Supported Live Online Not Supported In Person Not Supported
Company Information Replicate United States keepsake.ai/	Company Information PyTorch Founded: 2016 pytorch.org
Alternatives Azure Machine Learning Microsoft	Alternatives TensorFlow 5.0 out of 5 stars
TensorBoard Tensorflow	Core ML Apple
Flower	Create ML Apple
Weights & Biases	DeepSpeed Microsoft
Google Cloud Deep Learning VM Image Google View All	AWS Neuron Amazon Web Services View All
Categories Machine Learning Supported ML Experiment Tracking Supported Version Control Supported	Categories AI Development Supported AI/ML Model Training Supported Machine Learning Supported Neural Network Supported

Integrations Amazon S3 Supported Amazon SageMaker Debugger Not Supported Apolo Not Supported Coiled Not Supported EasyODM Not Supported Exafunction Not Supported Gemini Enterprise Agent Platform Notebooks Not Supported Giskard Not Supported Google Cloud Platform Not Supported Intel Tiber AI Cloud Not Supported JFrog ML Not Supported Keepsake Not Supported LTXV Not Supported Lightly Not Supported PaliGemma 2 Not Supported Qualcomm Cloud AI SDK Not Supported Runyour AI Not Supported Vast.ai Not Supported Zilliz Cloud Not Supported vLLM Not Supported Show More Integrations View All 7 Integrations	Integrations Amazon S3 Not Supported Amazon SageMaker Debugger Supported Apolo Supported Coiled Supported EasyODM Supported Exafunction Supported Gemini Enterprise Agent Platform Notebooks Supported Giskard Supported Google Cloud Platform Supported Intel Tiber AI Cloud Supported JFrog ML Supported Keepsake Supported LTXV Supported Lightly Supported PaliGemma 2 Supported Qualcomm Cloud AI SDK Supported Runyour AI Supported Vast.ai Supported Zilliz Cloud Supported vLLM Supported Show More Integrations View All 151 Integrations
Claim Keepsake and update features and information Claim Keepsake and update features and information	Claim PyTorch and update features and information Claim PyTorch and update features and information