FastText is one of the popular names in Word Embedding these days. In short, It is created by FaceBook. Still, FastText is open source so you don’t have to pay anything for commercial use. You may use FastText in many ways like test classification and text representation etc. While under this article , We will only explore the text representation . Basically for any Machine Learning algorithms on Text , You need to convert them into numbers vectors so you can categorize and find sense of the text. Lets understand How to create word embedding using FastText ?
Yes! FastText has its own implementation for word embedding . Here I am sharing the official link for FastText own implementation for word embedding .
Here you can use FastText pre train model as well as you may train your own model of embedding with fastText algorithms . For implementation prospective I will suggest you to visit the official FastText tutorial on embeddings .
Gensim provide the another way to apply FastText Algorithms and create word embedding .Here is the simple code example –
from gensim.models import FastText
from gensim.test.utils import common_texts
model_FastText = FastText(size=4, window=3, min_count=1)
model_FastText .train(sentences=common_texts, total_examples=len(common_texts), epochs=10)
The above example is of 4 line implementation. Let’s understand one by one –
4. The fourth line gives the last train command syntax for FastText .
When you read this title, you must have a question. Embedding on your training data or FastText Pre-trained Model. Actually, this is one of the big question points for every data scientist. Actually, there is a very clear line between these two. Let’s understand them one by one. See FastText is not a model, It’s an algorithm or Library which we use to train sentence embedding. However Pre train Fast Text Models are the ready-made solution ( models ) on some large corpus. This is the only beneficiary for generalize data itself.
See Training on large data involves heavy computation cost. Also, any deep learning model like FastText etc needs too much data.
Friends, how did you find this article – How to create word embedding using FastText? Please write your views on this topic. Apart from this article, There are some other key terms that you should understand when it comes to word embedding. Word Embedding is a very vast and hot research topic. So keep on the reading-related the latest content on this. Please refer to the below article for reference and basic understanding –
I hope this tutorial has helped you in understanding FastText in detail. If you have any queries then you can contact us for more help and information.