Update nlp.vectors to nlp.vocab.vectors
@@ -111,7 +111,7 @@ Check whether a key has been mapped to a vector entry in the table.
>
> ```python
> cat_id = nlp.vocab.strings["cat"]
-> nlp.vectors.add(cat_id, numpy.random.uniform(-1, 1, (300,)))
+> nlp.vocab.vectors.add(cat_id, numpy.random.uniform(-1, 1, (300,)))
> assert cat_id in vectors
> ```
@@ -315,7 +315,7 @@ performed in chunks, to avoid consuming too much memory. You can set the
>
> ```python
> queries = numpy.asarray([numpy.random.uniform(-1, 1, (300,))])
-> most_similar = nlp.vectors.most_similar(queries, n=10)
+> most_similar = nlp.vocab.vectors.most_similar(queries, n=10)
> ```
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