I have build a Keras model for next word prediction and I am trying to use my model in front-end for predicting next word based on input from the text field, I have to convert the following code from Python to JavaScript but did not find any suitable option. Is there any way to work around this?
from keras.preprocessing.sequence import pad_sequences
input_text = input().strip().lower()
encoded_text = tokenizer.texts_to_sequences([input_text])[0]
pad_encoded = pad_sequences([encoded_text], maxlen=seq_len, truncating='pre')
for i in (model.predict(pad_encoded)[0]).argsort()[-10:][::-1]:
pred_word = tokenizer.index_word[i]
print("Next word suggestion:",pred_word)
I am getting the following predictions for I in Python :
I just wrote an alternative in node.js, maybe it can help you
Repo: https://github.com/Shadowhusky/node_tokenizer
You can install it with
npm install --save tf_node_tokenizer
Example:
const { Tokenizer } = require("tf_node_tokenizer");
const tokenizer = new Tokenizer({ num_words: 5, oov_token = "<unk>", });
const text = [
"<start> Cake and frosting all over a face and hands tells a happy story. <end>",
"<start> A baby is feeding himself with his hands and is smeared with food. <end>",
"<start> A baby eating pink dessert in a highchair <end>"
];
tokenizer.fitOnTexts(text);
tokenizer.texts_to_sequences(text);
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