Install FastText for Text Classification in Python

FastText is a library for text classification and word representation. It is efficient and easy to use. This guide will help you install FastText in Python.

What is FastText?

FastText is developed by Facebook's AI Research team. It is designed for text classification and word embeddings. It works well with large datasets.

FastText is built on top of word2vec. It adds subword information. This helps in handling rare words better.

Prerequisites

Before installing FastText, ensure you have Python 3.6 or higher. You also need pip for package management.

Check your Python version using:

 
import sys
print(sys.version)

3.9.7 (default, Sep 16 2021, 16:59:28)

Install FastText

FastText can be installed using pip. Run the following command in your terminal:

pip install fasttext

If you face issues, try upgrading pip first:

pip install --upgrade pip

Verify Installation

After installation, verify it works. Open Python and import FastText:

 
import fasttext
print(fasttext.__version__)

0.9.2

Basic Text Classification Example

Here’s a simple example to classify text using FastText. First, prepare a training file.

Create a file named train.txt with labeled data:

__label__positive This is a great product.
__label__negative I dislike this item.

Train the model using the following code:

 
import fasttext

model = fasttext.train_supervised(input="train.txt")
model.save_model("model.bin")

This saves the trained model as model.bin.

Predict with FastText

Load the saved model and predict:

 
model = fasttext.load_model("model.bin")
print(model.predict("This is awesome"))

(('__label__positive',), array([0.99999994]))

Handling Common Issues

If you get errors, ensure your data is clean. FastText requires proper formatting.

For large datasets, consider using JAX for better performance.

Conclusion

FastText is a powerful tool for text classification. It is easy to install and use. Follow this guide to get started.

For more advanced workflows, check out LangChain or PyCaret.