universal sentence encoder - percent similarity

use.coffee

tf = require('@tensorflow/tfjs-node')
use = require('@tensorflow-models/universal-sentence-encoder')
use.load().then (model) ->
  sentences = [
    'Hello.'
    'Hi.'
    'Greetings.'
    'Sup?'
    "It's nice to meet you."
    'How are you?'
    'Hell'
  ]

  model.embed(sentences).then (embeddings) ->
    similarityMeasure =
      tf.matMul(embeddings, embeddings, false, true)
        .flatten()
        .slice(1, sentences.length - 1)

    console.log 'Percent similar to "Hello":'
    (await similarityMeasure.data()).map (percentage, index) ->
      console.log "#{(percentage * 100).toFixed(1)}% - #{sentences[index+1]}"

###
Percent similar to "Hello":
92.8% - Hi.
73.6% - Greetings.
72.0% - Sup?
55.2% - It's nice to meet you.
46.5% - How are you?
34.0% - Hell
###