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by PyTorch on 2018-06-16 (UTC).

FairSeq Toolkit - Major Update
- Distributed Training
- Transformer models (big Transformer on WMT Eng-German in < 5 hours on DGX-1)
- Fast Inference: translations @ 92 sent/sec for big Transformer
- Story Generation
Read more at Michael Auli's post: https://t.co/eptKDuh0WI pic.twitter.com/d4OtJZpdFw

— PyTorch (@PyTorch) June 16, 2018
pytorch
by PyTorch on 2018-06-16 (UTC).

code and pre-trained models to reproduce the recent paper "Scaling Neural Machine Translation" (https://t.co/mrRDmlwax1) where we train on up to 128 GPUs with half precision floating point operations as well as delayed batching.

— PyTorch (@PyTorch) June 16, 2018
pytorchw_codenlp

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