Paragraph Generator using BERT or GPT2019 Community Moderator ElectionNamed Entity Recognition: NLTK using Regular ExpressionSentiment analysis using pythonUsing Vowpal Wabbit for NERHow do “intent recognisers” work?Text comparison using word embeddingsMake a chatbot using slackResource and useful tips on Transfer Learning in NLPParagraph Vector - inference stage in the classificationWord classification (not text classification) using NLPIncrementally Train BERT with minimum QnA records - to get improved results
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Paragraph Generator using BERT or GPT
2019 Community Moderator ElectionNamed Entity Recognition: NLTK using Regular ExpressionSentiment analysis using pythonUsing Vowpal Wabbit for NERHow do “intent recognisers” work?Text comparison using word embeddingsMake a chatbot using slackResource and useful tips on Transfer Learning in NLPParagraph Vector - inference stage in the classificationWord classification (not text classification) using NLPIncrementally Train BERT with minimum QnA records - to get improved results
$begingroup$
I am trying to generate similar sentences, called paragraph generation. For example, what is the name of eldest brother of ram? - For this paragraphs can be - who is oldest brother of ram? , Who is oldest blood brother of ram? , I want to know eldest sibling of ram. etc etc
BERT and OpenAI GPT are one of most powerful NLP systems, as per my knowledge, atleast for now. However, I heard that BERT is based on MLM so cant be used for sentence generation, but can be used for word prediction.
Can OpenAI GPT be used for this purpose? If so, please give some pointer.
If any other name is in mind which is State of Art please suggest.
nlp bert
asked Mar 20 at 16:22
Sandeep BSandeep B
1067
$endgroup$
add a comment |
$begingroup$
I am trying to generate similar sentences, called paragraph generation. For example, what is the name of eldest brother of ram? - For this paragraphs can be - who is oldest brother of ram? , Who is oldest blood brother of ram? , I want to know eldest sibling of ram. etc etc
BERT and OpenAI GPT are one of most powerful NLP systems, as per my knowledge, atleast for now. However, I heard that BERT is based on MLM so cant be used for sentence generation, but can be used for word prediction.
Can OpenAI GPT be used for this purpose? If so, please give some pointer.
If any other name is in mind which is State of Art please suggest.
nlp bert
asked Mar 20 at 16:22
Sandeep BSandeep B
1067
$endgroup$
add a comment |
$begingroup$
I am trying to generate similar sentences, called paragraph generation. For example, what is the name of eldest brother of ram? - For this paragraphs can be - who is oldest brother of ram? , Who is oldest blood brother of ram? , I want to know eldest sibling of ram. etc etc
BERT and OpenAI GPT are one of most powerful NLP systems, as per my knowledge, atleast for now. However, I heard that BERT is based on MLM so cant be used for sentence generation, but can be used for word prediction.
Can OpenAI GPT be used for this purpose? If so, please give some pointer.
If any other name is in mind which is State of Art please suggest.
nlp bert
asked Mar 20 at 16:22
Sandeep BSandeep B
1067
$endgroup$
I am trying to generate similar sentences, called paragraph generation. For example, what is the name of eldest brother of ram? - For this paragraphs can be - who is oldest brother of ram? , Who is oldest blood brother of ram? , I want to know eldest sibling of ram. etc etc
BERT and OpenAI GPT are one of most powerful NLP systems, as per my knowledge, atleast for now. However, I heard that BERT is based on MLM so cant be used for sentence generation, but can be used for word prediction.
Can OpenAI GPT be used for this purpose? If so, please give some pointer.
If any other name is in mind which is State of Art please suggest.
nlp bert
nlp bert
asked Mar 20 at 16:22
Sandeep BSandeep B
1067
asked Mar 20 at 16:22
Sandeep BSandeep B
1067
asked Mar 20 at 16:22
Sandeep BSandeep B
1067
asked Mar 20 at 16:22
Sandeep BSandeep B
1067
asked Mar 20 at 16:22
Sandeep BSandeep B
1067
1067
add a comment |
add a comment |
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