在gensim中创建新的向量模型

from gensim.models import Word2Vec
from gensim.models.doc2vec import Doc2Vec, TaggedDocument

sentences = [["I", "love", "to", "code"], ["Machine", "learning", "is", "interesting"]]

model = Word2Vec(sentences, min_count=1)

documents = [TaggedDocument(doc, [i]) for i, doc in enumerate(sentences)]
model = Doc2Vec(documents, vector_size=100, window=5, min_count=1, epochs=10)

vector = model.wv['code']

similar_words = model.wv.most_similar('code')

similarity = model.wv.similarity('love', 'code')

vector = model.infer_vector(["I", "love", "to", "code"])