I’m using fasttext with a machine translation task.
The challenge I have is how to apply fasttext embedding with a small window less than the default value of .
SRC.build_vocab(train_data, vectors=Vectors(‘wiki.ar.vec’, url=url), unk_init = torch.Tensor.normal_, min_freq = 2)
I have found the below code but I’m not sure about how to build vocab using
from gensim.models import FastText model_ted = FastText(sentences_ted, size=300, window=5, min_count=5, workers=4,sg=1)