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  license: mit
 
 
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  license: mit
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+ datasets:
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+ - silicone
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  ---
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+
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+ This `KeyedVectors` model is specifically for `silicone:dyda_da`
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+
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+ ```python
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+ from gensim.models.keyedvectors import KeyedVectors
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+
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+ kv=KeyedVectors.load("silicone-dyda_da-utterance-tokens.wordvectors")
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+
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+ print(model.wv.most_similar_cosmul('peter',topn=25))
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+
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+ [('steven', 0.889095664024353),
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+ ('alice', 0.8783409595489502),
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+ ('li', 0.8624751567840576),
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+ ('benjamin', 0.8622595071792603),
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+ ('mrs', 0.8615201711654663),
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+ ('lin', 0.8603521585464478),
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+ ('david', 0.8597986698150635),
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+ ('dr', 0.8588740825653076),
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+ ('wang', 0.8527941107749939),
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+ ('mary', 0.8522424697875977),
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+ ('mike', 0.8521847724914551),
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+ ('john', 0.8494851589202881),
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+ ('michael', 0.84917151927948),
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+ ('linda', 0.8488836288452148),
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+ ('lucy', 0.8375136256217957),
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+ ('jane', 0.8359535336494446),
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+ ('monica', 0.834464430809021),
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+ ('smith', 0.8331072926521301),
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+ ('susan', 0.8329276442527771),
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+ ('zhang', 0.8323286771774292),
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+ ('professor', 0.8316935896873474),
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+ ('ellen', 0.8311569094657898),
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+ ('daniel', 0.8285720944404602),
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+ ('charles', 0.8285550475120544),
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+ ('james', 0.8280013203620911)]
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+ ```