How to use pre-trained word vectors with fastText on Linux?

To use pre-trained word vectors with fastText on Linux, you can follow these steps:

1. Download pre-trained word vectors: Download pre-trained word vectors in the fastText format from websites such as the fastText GitHub repository or the fastText website.
2. Convert the word vectors to fastText format: If the pre-trained word vectors are not in the fastText format, you can convert them using the fasttext command-line tool. For example, to convert a pre-trained word vector file glove.6B.100d.txt to the fastText format, you can run:

fasttext convert -input-format txt -output-format bin glove.6B.100d.txt model

1. Load the word vectors using the fastText Python API: In your Python code, load the pre-trained word vectors using the fasttext.load_model() function, specifying the path to the model file. For example, to load the converted pre-trained model from step 2, you can run:

import fasttext
model = fasttext.load_model('model.bin')

1. Use the word vectors in your code: You can now use the word vectors for tasks such as text classification, word similarity, and text generation. For example, to get the word vector for a word, you can run:

vector = model.get_word_vector('example')

That’s it! With these steps, you should be able to use pre-trained word vectors with fastText on Linux.