Add model_to_dict one-liner to word2vec notebook. Fix #1269
#1776
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I've created a small patch now @gojomo |
docs/notebooks/word2vec.ipynb
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| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "def model_to_dict():\n", |
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You no need this function for oneliner in notebook,
most_similars_precalc = {word : model.wv.most_similar(word) for word in model.wv.index2word} enough here
docs/notebooks/word2vec.ipynb
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| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Adding Word2Vec \"model to dict\" method to production pipeline" |
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Please add more motivation (why this can be useful, it will be good if you show concrete use-case, how you'll use most_similars_precalc )
menshikh-iv
changed the title
model_to_dict one-liner to word2vec notebook. Fix #1269
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Any changes required in the documentation? @menshikh-iv |
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@kakshay21 concrete example with comparison with/without caching |
docs/notebooks/word2vec.ipynb
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| "### Adding Word2Vec \"model to dict\" method to production pipeline\n", | ||
| "Suppose, we still want more performance improvement in production. \n", | ||
| "One good way is to cache all the similar words in a dictionary.\n", | ||
| "\n", |
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No needed \n after each sentence + you should add a link to the concrete issue in the notebook.
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Is it fine? @menshikh-iv |
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Thanks @kakshay21, congratz with the first contribution 🥇 |
Adding to the word2vec to production pipeline #1269