instantiated the Doc2Vec model like this
mv_tags_doc = [TaggedDocument(words=word_tokenize_clean(D), tags=[str(i)]) for i, D in enumerate(mv_tags_corpus)]
max_epochs = 50
vector_size = 20
alpha = 0.025
model = Doc2Vec(size=vector_size,
alpha=alpha,
min_alpha=0.00025,
min_count=1,
dm=0)
model.build_vocab(mv_tags_doc)
but getting error
TypeError: __init__() got an unexpected keyword argument 'size'
In the latest version of the Gensim library that you appear to be using, the parameter size
is now more consistently vector_size
everywhere. See the 'migrating to Gensim 4.0' help page:
Separately, if you're consulting any online example with that outdated parameter name, and which also suggested that unnecessary specification of min_alpha
and alpha
, there's a good chance the example you're following is a bad reference in other ways.
So, also take a look at this answer: My Doc2Vec code, after many loops of training, isn't giving good results. What might be wrong?