Hi! I have a question regarding using my own trained model (by using the sense2vec.train recipe) with prodigy for sense2vec (similarly to what is done here in the DEMO https://explosion.ai/demos/sense2vec). I've seen (and used) the example like the one below:
import spacy from sense2vec import Sense2VecComponent nlp = spacy.load('my_own_model') s2v = Sense2VecComponent('/path/to/reddit_vectors-1.1.0') nlp.add_pipe(s2v) doc = nlp("A sentence about natural language processing.") assert doc.text == 'natural language processing' freq = doc._.s2v_freq vector = doc._.s2v_vec most_similar = doc._.s2v_most_similar(3)
But I'm not quite sure how to use it by just inputting a single word (i.e. software) and use the doc = nlp("A sentence about natural language processing.") line (because I have no idea what to put there ), just want something similar to the standalone implementation of sense2vec but with my own model.
Thanks a lot