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Hello, I found you code calculate the masking using tf.not_equal(input_ids, 0), but in my vocab.txt, 0 refers to a character rather than , how to send manually constructed masking embedding to model?
The text was updated successfully, but these errors were encountered:
Hello, I found you code calculate the masking using tf.not_equal(input_ids, 0), but in my vocab.txt, 0 refers to a character rather than , how to send manually constructed masking embedding to model?
The text was updated successfully, but these errors were encountered: