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Fix "generator" language in word2vec docs #2935

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Sep 16, 2020
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Fix "generator" language in word2vec docs #2935

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b89be94
Fix docs about Word2Vec (fix #2934)
polm Sep 8, 2020
78eef97
Fix langauge to make it clear streaming is supported
polm Sep 8, 2020
652dcfb
Update gensim/models/word2vec.py
mpenkov Sep 16, 2020
c1191ae
Update CHANGELOG.md
mpenkov Sep 16, 2020
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -15,6 +15,7 @@ This release contains a major refactoring.
### :books: Tutorial and doc improvements

* Clear up LdaModel documentation - remove claim that it accepts CSC matrix as input (PR [#2832](https://github.com/RaRe-Technologies/gensim/pull/2832), [@FyzHsn](https://github.com/FyzHsn))
* Fix "generator" language in word2vec docs (PR [#2935](https://github.com/RaRe-Technologies/gensim/pull/2935), __[@polm](https://github.com/polm)__)

## :warning: 3.8.x will be the last gensim version to support Py2.7. Starting with 4.0.0, gensim will only support Py3.5 and above

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16 changes: 10 additions & 6 deletions gensim/models/word2vec.py
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Expand Up @@ -39,18 +39,22 @@

.. sourcecode:: pycon

>>> from gensim.test.utils import common_texts, get_tmpfile
>>> from gensim.test.utils import common_texts
>>> from gensim.models import Word2Vec
>>>
>>> path = get_tmpfile("word2vec.model")
>>>
>>> model = Word2Vec(common_texts, size=100, window=5, min_count=1, workers=4)
>>> model.save("word2vec.model")

The training is streamed, meaning `sentences` can be a generator, reading input data
from disk on-the-fly, without loading the entire corpus into RAM.

It also means you can continue training the model later:
The training is streamed, so ``sentences`` can be an iterable, reading input data
from disk on-the-fly. This lets you avoid loading the entire corpus into RAM.
However, note that because the iterable must be re-startable, `sentences` must
not be a generator. For an example of an appropriate iterator see
:class:`~gensim.models.word2vec.BrownCorpus`,
:class:`~gensim.models.word2vec.Text8Corpus` or
:class:`~gensim.models.word2vec.LineSentence`.

If you save the model you can continue training it later:

.. sourcecode:: pycon

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