garyw
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clinical-embeddings-100d-gl-cr

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garyw commited on Jan 31, 2023

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@@ -33,13 +33,13 @@ from gensim.models import FastText, Word2Vec, KeyedVectors # KeyedVectors are us
 model = KeyedVectors.load_word2vec_format('gl_100_cr.txt')
 # Return 100-dimensional vector representations of each word
-model.wv.word_vec('diabetes')
-model.wv.word_vec('cardiac_arrest')
-model.wv.word_vec('lymphangioleiomyomatosis')
 # Try out cosine similarity
-model.wv.similarity('copd', 'chronic_obstructive_pulmonary_disease')
-model.wv.similarity('myocardial_infarction', 'heart_attack')
-model.wv.similarity('lymphangioleiomyomatosis', 'lam')
 ```

 model = KeyedVectors.load_word2vec_format('gl_100_cr.txt')
 # Return 100-dimensional vector representations of each word
+model.word_vec('diabetes')
+model.word_vec('cardiac_arrest')
+model.word_vec('lymphangioleiomyomatosis')
 # Try out cosine similarity
+model.similarity('copd', 'chronic_obstructive_pulmonary_disease')
+model.similarity('myocardial_infarction', 'heart_attack')
+model.similarity('lymphangioleiomyomatosis', 'lam')
 ```