tensorspace
Neural network 3D visualization framework for interactive models in browsers
GraphCanon updated 3w · GitHub synced 3w · 27 views this month
Decision brief
A JavaScript framework enabling interactive browser-based 3D visualization for neural networks from TensorFlow, Keras, and TensorFlow.js.
Good fit when
- Project requires real-time visual insights into pre-trained deep learning models directly in web browsers.
- Development focuses on educational or explanatory content about machine learning with a need for intuitive model renderings.
Avoid when
- Team lacks expertise in JavaScript, as tensorspace primarily relies on this language for integration and execution.
- Project needs offline visualization capabilities since tensorspace operates exclusively within web browsers requiring internet access.
Observed Jul 14, 2026 · Source: enrich:decision_facts
Verify the decision
Adoption
Package downloads where a registry match exists. GitHub stars (5,191) are secondary evidence.
- npm downloads (30d)
- 159·npm downloads API·3w
Maintenance and security
Full trust report- Maintenance
- Dormant (1336d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
npm install tensorspaceSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A JavaScript-based neural network visualization tool that supports loading pre-trained deep learning models from TensorFlow, Keras, and TensorFlow.js and displaying them interactively within web browsers.
Capability facts
- MCP server
- No MCP server detected
Source: repo_scan · Aug 3, 2026
- Languages
- javascript
Source: github.language+package.json · Aug 3, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 3, 2026)
npm install tensorspaceSource link
Tags
README
Getting Started
Fig. 2 - TensorSpace Workflow
1. Install TensorSpace
Install in the Basic Case
- Step 1: Download Dependencies
Download dependencies build files TensorFlow.js (tf.min.js), Three.js (three.min.js), Tween.js (tween.min.js), TrackballControls (TrackballControls.js).
- Step 2: Download TensorSpace
Download TensorSpace build file tensorspace.min.js from Github, NPM, TensorSpace official website or CDN:
<script src="https://cdn.jsdelivr.net/npm/tensorspace@VERSION/dist/tensorspace.min.js"></script>
- Step 3: Include Build Files
Include all build files in web page.
<script src="tf.min.js"></script>
<script src="three.min.js"></script>
<script src="tween.min.js"></script>
<script src="TrackballControls.js"></script>
<script src="tensorspace.min.js"></script>
Install in the Progressive Framework
-
Step 1: Install TensorSpace
- Option 1: NPM
npm install tensorspace- Option 2: Yarn
yarn add tensorspace -
Step 2: Use TensorSpace
import * as TSP from 'tensorspace';
Checkout this Angular example for more information.
License
For agents
This page has a .md twin and JSON over the API.