@@ -7,18 +7,18 @@ This repository contains the code in both **PyTorch** and **TensorFlow** for our
...
@@ -7,18 +7,18 @@ This repository contains the code in both **PyTorch** and **TensorFlow** for our
>Preprint 2018
>Preprint 2018
#### TensorFlow
## TensorFlow
- The source code is in the `tf/` folder, supporting (1) single-node multi-gpu training, and (2) multi-host TPU training.
- The source code is in the `tf/` folder, supporting (1) single-node multi-gpu training, and (2) multi-host TPU training.
- Besides the source code, we also provide pretrained "TensorFlow" models with state-of-the-art (SoTA) performances reported in the paper.
- Besides the source code, we also provide pretrained "TensorFlow" models with state-of-the-art (SoTA) performances reported in the paper.
- Please refer to `tf/README.md` for details.
- Please refer to `tf/README.md` for details.
#### PyTorch
## PyTorch
- The source code is in the `pytorch/` folder, supporting single-node multi-gpu training via the module `nn.DataParallel`.
- The source code is in the `pytorch/` folder, supporting single-node multi-gpu training via the module `nn.DataParallel`.
- Please refer to `pytorch/README.md` for details.
- Please refer to `pytorch/README.md` for details.
#### Results
## Results
Transformer-XL achieves new state-of-the-art results on multipole language modeling benchmarks. Transformer-XL is also the first to break through the 1.0 barrier on char-level language modeling. Below is a summary.
Transformer-XL achieves new state-of-the-art results on multipole language modeling benchmarks. Transformer-XL is also the first to break through the 1.0 barrier on char-level language modeling. Below is a summary.
