Did you guys try to play with the generative and language modeling capabilities of the model also?
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Take a look at Transformer-XL model that can already generate coherent, novel text articles with thousands of tokens Code, pretrained models, paper:https://github.com/kimiyoung/transformer-xl …
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This might be the most important work of nlp in 2019
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we're only in June. I'm pretty sure there will be a revolution coming from FAIR or something.
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One comment though: you should specify the language you are working on. There is no indication on Github that the pre-trained model is for English. It may seem "obvious", but it has important methodological implications (has
@emilymbender has repeatedly pointed out). -
Benderruled! (Am I the first to verb it?)
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Any chance we'll see a pytorch version anytime soon?
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We work on a pytorch port
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Wow. The permutation operator used in self-attention is amazing. Split view in Figure 3 resonates with me a lot as I also tried to use a permutation operator in the listwise ranking loss in my ICML’18 paper: https://arxiv.org/pdf/1803.00114.pdf …
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Nice! Would be interesting to compare with vanilla Transformer trained using the new objective.
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