bert-extractive-summarizer
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Run Summarizer model on array of strings
Hi, How can I run the Summarizer model to predict an array of Strings. Predicting 1 string at a time using a for loop is very slow and not scalable for data with millions of rows. I get the following error when I pass an array:
model(df['text'].values[:1000], ratio=0.50)
ValueError: [E1041] Expected a string, Doc, or bytes as input, but got: <class 'numpy.ndarray'>.
Thanks.
I have a similar question. It would be ideal to have this summariser optimised for handling many instances at once or in parallel. As a likely common use case is to summarise many documents at once.
I am still stuck. Any help on this issue please ?