Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
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我已经搭建了一个用了bert embedding的的 cnn_model做classification。请问在我predict的时候如何可以输出 embedding之后的conv1d (Conv1D) 层的结果呢?这里不是指weight,而是直接在predict的过程中的每个node的值
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You must follow the issue template and provide as much information as possible. otherwise, this issue will be closed. 请按照 issue 模板要求填写信息。如果没有按照 issue 模板填写,将会忽略并关闭这个 issue
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[A clear and concise description of what you want to know.] 我已经搭建了一个用了bert embedding的的 cnn_model做classification。请问在我predict的时候如何可以输出 embedding之后的conv1d (Conv1D) 层的结果呢?这里不是指weight,而是直接在predict的过程中的每个node的值