KeepsakeReplicate
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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.
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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.
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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
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Not Supported
On-Premises
Not Supported
iPhone
Supported
iPad
Supported
Android
Supported
Chromebook
Not Supported
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Audience
Developers in need of a tool to manage their code and enhance the efficiency of their workflows
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Audience
Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationReplicate
United States
keepsake.ai/
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Company InformationPyTorch
Founded: 2016
pytorch.org
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Categories |
Categories |
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Integrations
AWS Elastic Fabric Adapter (EFA)
Not Supported
Alibaba Cloud
Not Supported
Amazon EC2 G5 Instances
Not Supported
ApertureDB
Not Supported
Dataoorts GPU Cloud
Not Supported
Domino Enterprise AI Platform
Not Supported
EasyODM
Not Supported
EdgeCortix
Not Supported
Exafunction
Not Supported
ExecuTorch
Not Supported
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Integrations
AWS Elastic Fabric Adapter (EFA)
Supported
Alibaba Cloud
Supported
Amazon EC2 G5 Instances
Supported
ApertureDB
Supported
Dataoorts GPU Cloud
Supported
Domino Enterprise AI Platform
Supported
EasyODM
Supported
EdgeCortix
Supported
Exafunction
Supported
ExecuTorch
Supported
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