KeepsakeReplicate
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Related Products
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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
TorchMetrics is a collection of 90+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. A standardized interface to increase reproducibility. It reduces boilerplate. distributed-training compatible. It has been rigorously tested. Automatic accumulation over batches. Automatic synchronization between multiple devices. You can use TorchMetrics in any PyTorch model, or within PyTorch Lightning to enjoy additional benefits. Your data will always be placed on the same device as your metrics. You can log Metric objects directly in Lightning to reduce even more boilerplate. Similar to torch.nn, most metrics have both a class-based and a functional version. The functional versions implement the basic operations required for computing each metric. They are simple python functions that as input take torch.tensors and return the corresponding metric as a torch.tensor. Nearly all functional metrics have a corresponding class-based metric.
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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
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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Audience
Developers in need of a tool to manage their code and enhance the efficiency of their workflows
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Audience
Anyone seeking a solution providing several PyTorch metrics implementations to create custom metrics
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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
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
Free
Free Version
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
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationReplicate
United States
keepsake.ai/
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Company InformationTorchMetrics
United States
torchmetrics.readthedocs.io/en/stable/
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Alternatives |
Alternatives |
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Categories |
Categories |
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Integrations
PyTorch
Supported
Amazon S3
Supported
Google Cloud Storage
Supported
JSON
Supported
Lightning AI
Not Supported
Python
Supported
TensorFlow
Supported
scikit-learn
Supported
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Integrations
PyTorch
Supported
Amazon S3
Not Supported
Google Cloud Storage
Not Supported
JSON
Not Supported
Lightning AI
Supported
Python
Not Supported
TensorFlow
Not Supported
scikit-learn
Not Supported
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