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Description

Keepsake is a Python library that is open-source and specifically designed for managing version control in machine learning experiments and models. It allows users to automatically monitor various aspects such as code, hyperparameters, training datasets, model weights, performance metrics, and Python dependencies, ensuring comprehensive documentation and reproducibility of the entire machine learning process. By requiring only minimal code changes, Keepsake easily integrates into existing workflows, permitting users to maintain their usual training routines while it automatically archives code and model weights to storage solutions like Amazon S3 or Google Cloud Storage. This capability simplifies the process of retrieving code and weights from previous checkpoints, which is beneficial for re-training or deploying models. Furthermore, Keepsake is compatible with a range of machine learning frameworks, including TensorFlow, PyTorch, scikit-learn, and XGBoost, enabling efficient saving of files and dictionaries. In addition to these features, it provides tools for experiment comparison, allowing users to assess variations in parameters, metrics, and dependencies across different experiments, enhancing the overall analysis and optimization of machine learning projects. Overall, Keepsake streamlines the experimentation process, making it easier for practitioners to manage and evolve their machine learning workflows effectively.

Description

Effortlessly switch between eager and graph modes using TorchScript, while accelerating your journey to production with TorchServe. The torch-distributed backend facilitates scalable distributed training and enhances performance optimization for both research and production environments. A comprehensive suite of tools and libraries enriches the PyTorch ecosystem, supporting development across fields like computer vision and natural language processing. Additionally, PyTorch is compatible with major cloud platforms, simplifying development processes and enabling seamless scaling. You can easily choose your preferences and execute the installation command. The stable version signifies the most recently tested and endorsed iteration of PyTorch, which is typically adequate for a broad range of users. For those seeking the cutting-edge, a preview is offered, featuring the latest nightly builds of version 1.10, although these may not be fully tested or supported. It is crucial to verify that you meet all prerequisites, such as having numpy installed, based on your selected package manager. Anaconda is highly recommended as the package manager of choice, as it effectively installs all necessary dependencies, ensuring a smooth installation experience for users. This comprehensive approach not only enhances productivity but also ensures a robust foundation for development.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

3LC No 
Amazon EC2 Capacity Blocks for ML No 
Amazon EC2 G5 Instances No 
Cameralyze No 
Cerebrium No 
Dataoorts GPU Cloud No 
Deeplake No 
EdgeCortix No 
Exafunction No 
GLM-5.2 No 
Google AI Edge No 
Horovod No 
Hugging Face Transformers No 
MegaETH No 
NeevCloud No 
Sesterce No 
SynapseAI No 
Vast.ai No 

Integrations

3LC Yes 
Amazon EC2 Capacity Blocks for ML Yes 
Amazon EC2 G5 Instances Yes 
Cameralyze Yes 
Cerebrium Yes 
Dataoorts GPU Cloud Yes 
Deeplake Yes 
EdgeCortix Yes 
Exafunction Yes 
GLM-5.2 Yes 
Google AI Edge Yes 
Horovod Yes 
Hugging Face Transformers Yes 
MegaETH Yes 
NeevCloud Yes 
Sesterce Yes 
SynapseAI Yes 
Vast.ai Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App Yes 
iPad App Yes 
Android App Yes 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Replicate

Country

United States

Website

keepsake.ai/

Vendor Details

Company Name

PyTorch

Founded

2016

Website

pytorch.org

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Version Control

Branch Creation / Deletion No 
Centralized Version History No 
Code Review No 
Code Version Management No 
Collaboration Tools No 
Compare / Merge Branches No 
Digital Asset / Binary File Storage No 
Isolated Code Branches No 
Option to Revert to Previous No 
Pull Requests No 
Roles / Permissions No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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