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Dear author,
I use this code
import sentencepiece as spm # import tensorflow_hub as hub import tensorflow as tf sp = spm.SentencePieceProcessor(model_file='assets/albertvi_30k-clean.model') input_ids = sp.encode("Tui rất là đẹp trai.") tags = set() # if is_training: # tags.add("train") # albert_module = hub.Module("./base", tags=tags, # trainable=False) with tf.Session() as sess: saver = tf.compat.v1.train.import_meta_graph('base/model.ckpt-1015000.meta') saver.restore(sess, 'base/model.ckpt-1015000.data-00000-of-00001') # graph = tf.get_default_graph() albert_inputs = dict( input_ids=input_ids, # input_mask=input_mask, # segment_ids=segment_ids ) # albert_outputs = model( # inputs=albert_inputs, # signature="tokens", # as_dict=True) # If you want to use the token-level output, use # albert_outputs["sequence_output"] instead. # output_layer = albert_outputs["pooled_output"]
But It has an error
err, "a mismatch between the current graph and the graph")
The text was updated successfully, but these errors were encountered:
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Dear author,
I use this code
But It has an error
err, "a mismatch between the current graph and the graph")
The text was updated successfully, but these errors were encountered: