Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Gemini Enterprise Agent Platform Reviews & Ratings
    1,161 Ratings
    Company Website
  • Fraud.net Reviews & Ratings
    56 Ratings
    Company Website
  • Qloo Reviews & Ratings
    23 Ratings
    Company Website
  • Anaconda Reviews & Ratings
    625 Ratings
    Company Website
  • Google AI Studio Reviews & Ratings
    41 Ratings
    Company Website
  • Runpod Reviews & Ratings
    230 Ratings
    Company Website
  • Google Cloud BigQuery Reviews & Ratings
    2,027 Ratings
    Company Website
  • TIMi Reviews & Ratings
    68 Ratings
    Company Website
  • kama.ai Reviews & Ratings
    9 Ratings
  • SCIKIQ Reviews & Ratings
    14 Ratings
    Company Website

What is tensorViz?

tensorViz offers a unique platform that allows developers to explore PyTorch models and JAX/Flax programs through interactive graph visualizations. For PyTorch, users can delve into nested modules, inspect tensor shapes captured during a single forward pass, navigate to the related Python source code, and witness architectural changes along with code variations. The platform also includes pre-recorded model graphs that can be analyzed without any installation requirements. A free extension compatible with VS Code is available on both the Visual Studio Marketplace and Open VSX. To enable local capture, users need to have Python installed along with the relevant model dependencies and sample inputs. Additionally, there are standalone coding-agent plugins in preview specifically designed for Apple Silicon macOS, allowing MCP agents to connect seamlessly with the extension. While JAX/Flax graphs rely on CPU tracing to determine shapes, it's crucial to understand that source modifications for PyTorch models do not apply in this scenario. By providing a cohesive experience for both frameworks, tensorViz significantly improves the development and debugging workflow for its users, ultimately leading to more efficient coding practices. This dual framework support ensures that developers have the tools they need to effectively manage their projects and enhance their productivity.

What is Keepsake?

Keepsake is an open-source Python library tailored for overseeing version control within machine learning experiments and models. It empowers users to effortlessly track vital elements such as code, hyperparameters, training datasets, model weights, performance metrics, and Python dependencies, thereby facilitating thorough documentation and reproducibility throughout the machine learning lifecycle. With minimal modifications to existing code, Keepsake seamlessly integrates into current workflows, allowing practitioners to continue their standard training processes while it takes care of archiving code and model weights to cloud storage options like Amazon S3 or Google Cloud Storage. This feature simplifies the retrieval of code and weights from earlier checkpoints, proving to be advantageous for model re-training or deployment. Additionally, Keepsake supports a diverse array of machine learning frameworks including TensorFlow, PyTorch, scikit-learn, and XGBoost, which aids in the efficient management of files and dictionaries. Beyond these functionalities, it offers tools for comparing experiments, enabling users to evaluate differences in parameters, metrics, and dependencies across various trials, which significantly enhances the analysis and optimization of their machine learning endeavors. Ultimately, Keepsake not only streamlines the experimentation process but also positions practitioners to effectively manage and adapt their machine learning workflows in an ever-evolving landscape. By fostering better organization and accessibility, Keepsake enhances the overall productivity and effectiveness of machine learning projects.

Media

No images available

Media

Integrations Supported

Claude Code
Codex CLI
Cursor
GitHub
Model Context Protocol (MCP)
T3 Code
Visual Studio Code

Integrations Supported

Amazon S3
Google Cloud Storage
JSON
PyTorch
Python
TensorFlow
scikit-learn

API Availability

Has API

API Availability

Has API

Pricing Information

$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

Pricing Information

Free
Free Version

Supported Platforms

SaaS
Windows
Mac
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

tensorViz

Company Website

tensorviz.dev/

Company Facts

Organization Name

Replicate

Company Location

United States

Company Website

keepsake.ai/

Categories and Features

Deep Learning

Not specified

Machine Learning

Not specified

Categories and Features

Machine Learning

Not specified

Version Control

Not specified

Popular Alternatives

AWS Neuron Reviews & Ratings

AWS Neuron

Amazon Web Services

Popular Alternatives

TensorBoard Reviews & Ratings

TensorBoard

Tensorflow