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make RoBERTa usable in more tasks including QA #1017
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Summary: Pull Request resolved: facebookresearch#1017 Currently Roberta encoder, model and tensorizer are pretty stand-alone, not conforming to other PyText tasks. This diff is an attempt to better integrate it. It involves the following: - Make GPT-2 BPE act like a proper tokenizer and also return char indices. This makes Roberta tensorizer more modular so code can be re-used - Make Roberta tensorizer conform more closely to BERTTensorizer so that the TransformerSentenceEncoder interfaces are better aligned. - Add a Roberta tensorizer for question answering Differential Revision: D17690805 fbshipit-source-id: fc7872098e5a654e1da2c8d4878be56535991c60
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This pull request was exported from Phabricator. Differential Revision: D17690805 |
Summary: Pull Request resolved: facebookresearch#1017 Currently Roberta encoder, model and tensorizer are pretty stand-alone, not conforming to other PyText tasks. This diff is an attempt to better integrate it. It involves the following: - Make GPT-2 BPE act like a proper tokenizer and also return char indices. This makes Roberta tensorizer more modular so code can be re-used - Make Roberta tensorizer conform more closely to BERTTensorizer so that the TransformerSentenceEncoder interfaces are better aligned. - Add a Roberta tensorizer for question answering Differential Revision: D17690805 fbshipit-source-id: a7c6d10497f2c0a0cdf7bdffe843e4c64384d5c1
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This pull request was exported from Phabricator. Differential Revision: D17690805 |
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Summary: Pull Request resolved: facebookresearch#1017 Currently Roberta encoder, model and tensorizer are pretty stand-alone, not conforming to other PyText tasks. This diff is an attempt to better integrate it. It involves the following: - Make GPT-2 BPE act like a proper tokenizer and also return char indices. This makes Roberta tensorizer more modular so code can be re-used - Make Roberta tensorizer conform more closely to BERTTensorizer so that the TransformerSentenceEncoder interfaces are better aligned. - Add a Roberta tensorizer for question answering Differential Revision: D17690805 fbshipit-source-id: 3c774429ed97598094d657c3069bd9865dc46f27
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Summary: Pull Request resolved: facebookresearch#1017 Currently Roberta encoder, model and tensorizer are pretty stand-alone, not conforming to other PyText tasks. This diff is an attempt to better integrate it. It involves the following: - Make GPT-2 BPE act like a proper tokenizer and also return char indices. This makes Roberta tensorizer more modular so code can be re-used - Make Roberta tensorizer conform more closely to BERTTensorizer so that the TransformerSentenceEncoder interfaces are better aligned. - Add a Roberta tensorizer for question answering Differential Revision: D17690805 fbshipit-source-id: e97fe1352047e8d915005a3fcdd76bd53b268a03
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This pull request has been merged in 3fd9764. |
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Summary:
Currently Roberta encoder, model and tensorizer are pretty stand-alone, not conforming to other PyText tasks. This diff is an attempt to better integrate it.
It involves the following:
Differential Revision: D17690805