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+ ---
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+ tags:
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+ - word2vec
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+ language: ta
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+ license: gpl-3.0
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+ ---
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+
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+ ## Description
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+ Word embedding model trained by Al-Rfou et al.
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+
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+
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+ ## How to use?
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+
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+ ```
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+ import pickle
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+ from numpy import dot
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+ from numpy.linalg import norm
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+ from huggingface_hub import hf_hub_download
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+ words, embeddings = pickle.load(open(hf_hub_download(repo_id="Word2vec/polyglot_words_embeddings_en", filename="words_embeddings_en.pkl"), 'rb'),encoding="latin1")
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+
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+ word = "Irish"
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+ a = embeddings[words.index(word)]
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+ most_similar = []
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+ for i in range(len(embeddings)):
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+ if i != words.index(word):
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+ b = embeddings[i]
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+ cos_sim = dot(a, b)/(norm(a)*norm(b))
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+ most_similar.append(cos_sim)
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+ else:
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+ most_similar.append(0)
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+
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+ words[most_similar.index(max(most_similar))]
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+ ```
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+
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+ ## Citation
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+
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+ ```
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+ @InProceedings{polyglot:2013:ACL-CoNLL,
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+ author = {Al-Rfou, Rami and Perozzi, Bryan and Skiena, Steven},
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+ title = {Polyglot: Distributed Word Representations for Multilingual NLP},
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+ booktitle = {Proceedings of the Seventeenth Conference on Computational Natural Language Learning},
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+ month = {August},
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+ year = {2013},
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+ address = {Sofia, Bulgaria},
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+ publisher = {Association for Computational Linguistics},
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+ pages = {183--192},
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+ url = {http://www.aclweb.org/anthology/W13-3520}
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+ }
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+ ```