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💫 Industrial-strength Natural Language Processing (NLP) in Python
180 Commits 66 Branches 174 Tags 277 MiB
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0f6bf2a2ee
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Matthew Honnibal 0f6bf2a2ee * Fix niggling memory error, which was caused by bug in the way tokens resized their internal vector.
2014-09-15 02:08:39 +02:00
data * Tests passing for new Word object version 2014-08-24 18:13:53 +02:00
docs * Tweak overview docs 2014-09-07 21:29:41 +02:00
spacy * Fix niggling memory error, which was caused by bug in the way tokens resized their internal vector. 2014-09-15 02:08:39 +02:00
tests * Update tokenization tests for new tokenizer rules 2014-09-15 01:32:51 +02:00
.gitignore * Upd gitignore 2014-08-20 17:04:33 +02:00
fabfile.py * Only store LexemeC structs in the vocabulary, transforming them to Lexeme objects for output. Moving away from Lexeme objects for Tokens soon. 2014-09-11 12:28:38 +02:00
README.md Initial commit 2014-07-04 01:15:40 +10:00
requirements.txt * Temporarily remove sparsehash requirement 2014-08-20 17:12:19 +02:00
setup.py * PointerHash working, efficiency is good. 6-7 mins 2014-09-13 16:43:59 +02:00

README.md

spaCy

Lightning fast, full-cream NL tokenization. Tokens are pointers to rich Lexeme structs.