Update rollup config and readme information

Author: Kevin Scott

README.md

@@ -2,6 +2,8 @@
 
 ML Classifier is a machine learning engine for quickly training image classification models in your browser. Models can be saved with a single command, and the resulting models reused to make image classification predictions.
 
+This package is intended as a companion for [`ml-classifier-ui`](https://github.com/thekevinscott/ml-classifier-ui), which provides a web frontend in React for uploading data and seeing results.
+
 ## Getting Started
 
 ### Installation
@@ -171,6 +173,8 @@ mlClassifier.save(('path-to-save');
 #### Parameters
 
 * **handlerOrUrl** (`io.IOHandler | string`) *Optional* - an argument to be passed to `model.save`. If omitted, the model's unique labels will be concatenated together in the form of `class1-class2-class3`.
+* **params** (`Object`) *Optional* - a set of parameters that will be passed directly to `model.save`. [View the Tensorflow.JS docs](https://js.tensorflow.org/api/0.12.0/#tf.Model.save) for an up-to-date list of arguments.
+
 
 ## `getModel`
 

package.json

@@ -1,6 +1,6 @@
 {
   "name": "ml-classifier",
-  "version": "0.3.1",
+  "version": "0.3.3",
   "description": "A machine learning engine for quickly training image classification models in your browser",
   "main": "dist/index.js",
   "typings": "dist/index.d.ts",
@@ -9,7 +9,6 @@
     "clean": "rimraf dist/*",
     "watch": "npm run build -- --watch",
     "build": "npm run clean && rollup -c",
-    "publish": "npm run build && npm publish",
     "test": "jest"
   },
   "keywords": [

rollup.config.js

@@ -2,11 +2,14 @@
 import typescript from 'rollup-plugin-typescript2';
 
 export default {
-  entry: './src/index.ts',
+  input: './src/index.ts',
   output: {
     name: 'MLClassifier',
     file: './dist/index.js',
-    format: 'umd',
+    format: 'es',
+    external: [
+      '@tensorflow/tfjs',
+    ],
   },
   plugins: [
     typescript({

src/index.ts

@@ -30,7 +30,6 @@ class MLClassifier {
   private data: IData = {
     classes: {},
   };
-  public tf = tf;
 
   constructor() {
     this.init();
@@ -170,13 +169,13 @@ class MLClassifier {
   }
 
   // handlerOrURL?: tf.io.IOHandler | string;
-  public save = async(handlerOrURL?: string) => {
+  public save = async(handlerOrURL?: string, params: IParams = {}) => {
     await this.loaded();
     if (!this.model) {
       throw new Error('You must call train prior to calling save');
     }
 
-    return await this.model.save(handlerOrURL || getDefaultDownloadHandler(this.data.classes));
+    return await this.model.save(handlerOrURL || getDefaultDownloadHandler(this.data.classes), params);
   }
 }