BrikerMan
/ nlp_get_all_non_chinese_tokens.py
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November 18, 2018 10:43
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| # encoding: utf-8 | |
| """ | |
| @author: BrikerMan | |
| @contact: eliyar917@gmail.com | |
| @blog: https://eliyar.biz | |
| @version: 1.0 | |
| @license: Apache Licence | |
| @file: pre_process | |
| @time: 2018/11/18 |
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BrikerMan
/ kashgar_chinese_ner.ipynb
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April 10, 2020 21:04
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BrikerMan
/ ios-env-check.sh
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April 15, 2021 04:47
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| report=$( mktemp ) | |
| echo "# Environment Debugging" >> $report | |
| echo "" >> $report | |
| echo $"This file will generate an report file Yodo1 for debugging." >> $report | |
| echo "" >> $report | |
| echo $"## Pod Environment" >> $report | |
| echo $"`pod env`" >> $report | |
| echo "" >> $report | |
| echo $"### Podfile.lock" >> $report |
BrikerMan
/ w2v_visualizer-v2.py
Last active
March 30, 2022 20:26
Convert gensim word2vec to tensorboard visualized model, detail: https://eliyar.biz/using-pre-trained-gensim-word2vector-in-a-keras-model-and-visualizing/
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| from gensim.models import KeyedVectors | |
| # Load gensim word2vec | |
| w2v_path = '<Gensim File Path>' | |
| w2v = KeyedVectors.load_word2vec_format(w2v_path) | |
| import io | |
| # Vector file, `\t` seperated the vectors and `\n` seperate the words | |
| """ |
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