PyTorch nn.DistributedDataParallel

October 12, 2019October 12, 2019 by admin

https://yangkky.github.io/2019/07/08/distributed-pytorch-tutorial.html

ShujianFollow

Nick Ryder (an author of GPT-3) gives a talk on GPT-3, in which he discusses a lot of things not written in the paper. W&B talks like this are highly underrated with full of great MLers. Don't forget to check other talks, too.

https://t.co/CcWWB6iO1e

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Emanuele Rossi @emaros96·

5 Aug

The code for our recent paper "TGN: Temporal Graph Networks" is live on Github: https://t.co/5NZPOZnPJ9 !
Paper link: https://t.co/1gUTxlC3pr
Joint work w/ @mmbronstein @frederickmonti @b_p_chamberlain @ffabffrasca @aittalam

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Amanda Askell @AmandaAskell·

5 Aug

The internet: We have no idea how good GPT-3 is because all of the outputs are cherry-picked.

Me, who made sure the human evaluation experiments in the paper didn't involve any cherry-picking: 😢

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Suraj Patil @psuraj28·

5 Aug

ONNXT5: accelerated inference for T5, built using
@onnxruntime and @huggingface transformers.
Run any of the T5 trained tasks (translation, summarization, sentiment analysis, completion, generation) at blazing speed 🔥. Built by Abel
https://t.co/m18PjNHFug

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Leo Boytsov @srchvrs·

5 Aug

"Deep metric learning papers have consistently claimed great advances in acc. We take closer look to see if it is actually true. We find flaws in experimental methodology of numerous metric learning papers & show that actual improvements over time have been marginal at best." https://t.co/cTOPgpmg9x

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