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readme update
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v4ikin committed Mar 14, 2019
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2 changes: 1 addition & 1 deletion README.md
Expand Up @@ -15,7 +15,7 @@ This approach enables creation of an embedding in vector space for any sequence
Chars2vec models does not keep any dictionary of embeddings,
but generates embedding vectors inplace using pretrained model.

There are pretrained models of dimensions 50, 100 and 150 for the English language.
There are pretrained models of dimensions 50, 100, 150, 200 and 300 for the English language.
The library provides convenient user API to train a model for an arbitrary set of characters.
Read more details about the architecture of [Chars2vec:
Character-based language model for handling real world texts with spelling
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2 changes: 1 addition & 1 deletion setup.py
Expand Up @@ -30,7 +30,7 @@
This approach enables creation of an embedding in vector space for any sequence of characters.\
Chars2vec models does not keep any dictionary of embeddings, \
but generates embedding vectors inplace using pretrained model. \
There are pretrained models of dimensions 50, 100 and 150 for the English language.\
There are pretrained models of dimensions 50, 100, 150, 200 and 300 for the English language.\
The library provides convenient user API to train a model for an arbitrary set of characters.',
classifiers=['Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3']
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