修改验证集
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# bert-utils
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本文基于Google开源的[BERT]()代码进行了进一步的简化,方便生成句向量与做文本分类
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本文基于Google开源的[BERT](https://github.com/google-research/bert)代码进行了进一步的简化,方便生成句向量与做文本分类
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1、下载BERT中文模型
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@ -664,13 +664,13 @@ class BertSim:
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if __name__ == '__main__':
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sim = BertSim()
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# sim.set_mode(tf.estimator.ModeKeys.TRAIN)
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# sim.train()
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# sim.set_mode(tf.estimator.ModeKeys.EVAL)
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# sim.eval()
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sim.set_mode(tf.estimator.ModeKeys.PREDICT)
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while True:
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sentence1 = input('sentence1: ')
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sentence2 = input('sentence2: ')
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predict = sim.predict(sentence1, sentence2)
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print(f'similarity:{predict[0][1]}')
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sim.set_mode(tf.estimator.ModeKeys.TRAIN)
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sim.train()
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sim.set_mode(tf.estimator.ModeKeys.EVAL)
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sim.eval()
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# sim.set_mode(tf.estimator.ModeKeys.PREDICT)
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# while True:
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# sentence1 = input('sentence1: ')
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# sentence2 = input('sentence2: ')
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# predict = sim.predict(sentence1, sentence2)
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# print(f'similarity:{predict[0][1]}')
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