I tried to generate sentences using Flair, which is a super convenient NLP library, but I couldn't do that in the first place. From the name of TextRegressor, it seems that it will somehow regress and generate sentences ...? Flair is insanely convenient, but there aren't many articles in Japanese, so I'll write an article even if it's not a big deal.
https://github.com/ochiba0227/flair_text_regressor
It doesn't appear in the Flair tutorial either, so TextRegressor test code and [TextRegressor model implementation](https: / I read from /github.com/flairNLP/flair/blob/master/flair/models/text_regression_model.py) and prepared a sentence labeled as follows. It seems that only float type can be used for the label, so I put the same number for the time being. Perhaps you can learn the articles generated by label, but this time we will learn everything with a mess.
label_topic text
1 To solve the problem that an error message is displayed every time Windows starts.
If it is a 1-key case, the German-made "Wunderkey" is multifunctional and recommended for outdoor activities!
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Divide the data created above into train.tsv, dev.tsv, test.tsv.
Place the file in resources / data and run my_text_regressor.py.
This time, we will generate a document that starts with `when Windows starts. The results are as follows.
# create example sentence
sentence = Sentence('When Windows starts', use_tokenizer=japanese_tokenizer)
print(sentence.to_tokenized_string())
# predict tags and print
regressor.predict(sentence)
sentence.to_dict()
{'entities': [],
'labels': [{'confidence': 1.0, 'value': '0.8864221572875977'}],
'text': 'When Windows starts'}
Oh, the text was just vectorized ...? What a mess.
Since there is no tutorial, it was a little troublesome to read the source code ... I get an error message during learning, so it's probably still a feature under development. To be honest, it took about an hour, but I felt sad ... It's not so good to do it with momentum. It's regrettable that I can't do it, so next time I'd like to use GPT-2 quietly and try to generate sentences.
It seems that some people have already learned the Japanese Wikipedia corpus. https://qiita.com/tanreinama/items/3b73fdeff09dfe74ef52
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