Keepsake vs. tensorViz 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 tensorViz helps developers explore PyTorch models and JAX/Flax programs as interactive graphs. For PyTorch, users can expand nested modules, inspect tensor shapes captured from one forward pass, jump to Python source, and review architecture changes beside code diffs. The website offers recorded model graphs to explore without installation. The free VS Code extension is available from the Visual Studio Marketplace and Open VSX. Local capture requires Python, model dependencies, and example inputs. Standalone coding-agent plugins are an Apple Silicon macOS preview; MCP agents can also connect to the extension. JAX/Flax graphs use CPU tracing with inferred shapes, and PyTorch source edits are unavailable for them.
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 Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Developers in need of a tool to manage their code and enhance the efficiency of their workflows	Audience Machine learning engineers, PyTorch developers, researchers and students exploring model architecture, tensor shapes and architecture changes.
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 View more images or videos	Screenshots and Videos No images available
Pricing Free Free Version Supported Free Trial Not Supported	Pricing $0 The VS Code extension is free to install. Core graph exploration and source-edit forms work without an agent or provider API key; connecting a coding agent is optional. 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 Replicate United States keepsake.ai/	Company Information tensorViz tensorviz.dev/
Alternatives Azure Machine Learning Microsoft	Alternatives AWS Neuron Amazon Web Services
TensorBoard Tensorflow	TorchMetrics
Flower	PyTorch
Weights & Biases	Google Cloud Deep Learning VM Image Google
Google Cloud Deep Learning VM Image Google View All	Amazon EC2 Trn1 Instances Amazon View All
Categories Machine Learning Supported ML Experiment Tracking Supported Version Control Supported	Categories Deep Learning Supported Machine Learning Supported

Integrations Amazon S3 Supported Claude Code Not Supported Codex CLI Not Supported Cursor Not Supported GitHub Not Supported Google Cloud Storage Supported JSON Supported Model Context Protocol (MCP) Not Supported PyTorch Supported Python Supported T3 Code Not Supported TensorFlow Supported Visual Studio Code Not Supported scikit-learn Supported Show More Integrations View All 7 Integrations	Integrations Amazon S3 Not Supported Claude Code Supported Codex CLI Supported Cursor Supported GitHub Supported Google Cloud Storage Not Supported JSON Not Supported Model Context Protocol (MCP) Supported PyTorch Not Supported Python Not Supported T3 Code Supported TensorFlow Not Supported Visual Studio Code Supported scikit-learn Not Supported Show More Integrations View All 7 Integrations
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