code: def transformer_big():
    
    hparams = transformer_base()
    hparams.hidden_size = 1024
    hparams.filter_size = 4096
    # Reduce batch size to 2048 from 4096 to be able to train the model on a GPU
    # with 12 GB memory. For example, NVIDIA TITAN V GPU.
    hparams.batch_size = 2048
    hparams.num_heads = 16
    hparams.layer_prepostprocess_dropout = 0.3
    return hparams
docs: HParams for transformer big model on WMT.