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NatML for JavaScript
Zero Configuration Machine Learning Deployment
NatML is a platform that brings extremely easy and quick machine learning to JavaScript. It allows you to run ML-powered features in your JS application--browser or NodeJS--without managing any ML infrastructure. In a few steps:
First, fetch a model:
// Fetch the ResNet image classifier model data
const modelData = await MLModelData.fromHub("@natsuite/resnet18");
// Create the model
const model = modelData.deserialize();
Then create a predictor to make predictions with the model:
// Create the ResNet classifier predictor
const predictor = new ResNet18Predictor(model, modelData.labels);
Finally, make predictions with the predictor:
// Create an image feature
const imageFeature = new MLImageFeature("/path/to/cat 🐱.jpg");
// Classify the cat image with our predictor
const [label, score] = await predictor.predict(imageFeature);
// Log the results to the console
console.log(`Our image contains a ${label} with confidence ${score}`);
NatML is designed for developers to quickly integrate ML functionality into their applications without any knowledge or effort put into building or managing ML infrastructure. Features include:
- Extremely Easy to Use. NatML exposes machine learning models with simple functions that return familiar data types.
- Bare Metal Performance. NatML runs predictions on powerful GPU's with incredibly high memory and network bandwidth, giving you the highest performance and minimal latency.
- Latest Models. NatML Hub offers a growing catalog of the latest ML models being published from research labs around the world.
- Computer Vision. NatML supports models for object classification, object detection, semantic segmentation, style transfer, and so much more.
- Lightweight Package. NatML is distributed in a self-contained package weighing less than 100kb, with minimal external dependencies and no setup necessary.
# Install NatML
npm i natml --save
npm: natml
npm
Get NatML on NPM
Last modified 1yr ago