New answers tagged

0

Let’s use a pre-trained model rather than training our own word embeddings. For this, you can download pre-trained vectors from here. Each line of this file contains a word and it’s a corresponding n-dimensional vector. We will create a dictionary using this file for mapping each word to its vector representation. from gensim.models import FastText def ...


0

I really wanted to use gensim, but ultimately found that using the native fasttext library worked out better for me. The following code you can copy/paste into google colab and will work, out of the box: pip install fasttext import fasttext.util fasttext.util.download_model('en', if_exists='ignore') # English ft = fasttext.load_model('cc.en.300.bin') ...


Top 50 recent answers are included