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import * as tf from '@tensorflow/tfjs'; | |
import '@tensorflow/tfjs-node'; | |
import * as use from '@tensorflow-models/universal-sentence-encoder'; |
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[ | |
{ | |
"text": "buy", | |
"intent": "buy" | |
}, | |
{ | |
"text": "buying", | |
"intent": "buy" | |
}, | |
{ |
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[ | |
{ | |
"text": "Woah yess❤️❤️", | |
"intent": "none" | |
}, | |
{ | |
"text": "Happy birthday to the most beautiful woman on Instagram ! 💗💗", | |
"intent": "none" | |
}, | |
{ |
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[ | |
{ | |
"text": "where can I buy your dress?", | |
"intent": "buy" | |
}, | |
{ | |
"text": "how much was that dress?", | |
"intent": "buy" | |
}, | |
{ |
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import * as tf from '@tensorflow/tfjs'; | |
import '@tensorflow/tfjs-node'; | |
import * as use from '@tensorflow-models/universal-sentence-encoder'; | |
import comments from './comment-training.json'; | |
import comment_testing from './comment-test.json'; |
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const encodeData = data => { | |
const sentences = data.map(comment => comment.text.toLowerCase()); | |
const trainingData = use.load() | |
.then(model => { | |
return model.embed(sentences) | |
.then(embeddings => { | |
return embeddings; | |
}); | |
}) | |
.catch(err => console.error('Fit Error:', err)); |
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const outputData = tf.tensor2d(comments.map(comment => [ | |
comment.intent === 'buy' ? 1 : 0, | |
comment.intent === 'none' ? 1 : 0, | |
])); | |
// Output: [1,0] or [0,1] |
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const model = tf.sequential(); | |
// Add layers to the model | |
model.add(tf.layers.dense({ | |
inputShape: [512], | |
activation: 'sigmoid', | |
units: 2, | |
})); | |
model.add(tf.layers.dense({ |
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function run() { | |
Promise.all([ | |
encodeData(comments), | |
encodeData(comment_testing) | |
]) | |
.then(data => { | |
const { | |
0: training_data, | |
1: testing_data, | |
} = data; |
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name: Production Build | |
on: | |
pull_request: | |
push: | |
branches: | |
- master |
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