{skjs●n-js}

Zero dependencies. 100% mathematical accuracy (i think). Run your JSON models natively in any JS environment.

Installation

npm install skjson-js

Capabilities

Universal

Works in React, Vue, Vanilla JS, Node.js, and edge environments.

Type-Safe

Written in TypeScript, providing full autocomplete for `.predict()` and `.predict_proba()`.

Interactive Inference Demo

Try classifying an Iris flower (Random Forest model):

Sepal Length

Sepal Width

Petal Length

Petal Width

import { loadModel } from 'skjson-js';
import modelJson from './model.json';

const predictor = loadModel(modelJson);

// Running inference
const input = [[5.1, 3.5, 1.4, 0.2]];
const prediction = predictor.predict(input);

console.log("Predicted Class:", prediction[0]);

Preprocessing Execution (in progress)

If you exported a preprocessing model like `StandardScaler`, you can use the `.transform()` method natively:

const scaler = loadModel(scalerData)
const scaledFeatures = scaler.transform([[5.1, 3.5, 1.4, 0.2]])
console.log(scaledFeatures)

Roadmap

Load and infer common sklearn models
Completed
Load and infer pipeline json
Ongoing
Load and infer neural network json
Idle

Load and infer common sklearn models
Completed
Load and infer pipeline json
Ongoing
Load and infer neural network json
Idle