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--- |
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tags: |
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- word2vec |
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language: zhc |
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license: gpl-3.0 |
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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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## How to use? |
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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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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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words[most_similar.index(max(most_similar))] |
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``` |
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## Citation |
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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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``` |
