transformer
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Bidirectional RNN
Is there a way to train a bidirectional RNN (like LSTM or GRU) on trax nowadays?
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https://github.com/PaddlePaddle/PaddleNLP/tree/develop/examples/machine_translation/transformer
在我们的基于 Transformer 的 Machine Translation 例子中,数据准备这一步奏仅提供了
chooses 15% of token
From paper, it mentioned
Instead, the training data generator chooses 15% of tokens at random, e.g., in the sentence my
dog is hairy it chooses hairy.
It means that 15% of token will be choose for sure.
From https://github.com/codertimo/BERT-pytorch/blob/master/bert_pytorch/dataset/dataset.py#L68,
for every single token, it has 15% of chance that go though the followup procedure.
PositionalEmbedding
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Feature request
Is the addition of the 'OPTforSequenceClassification' class scheduled?
Is someone handling it?
When adding these functions, I wonder if it is possible to PR one by one, or if I have to PR all classes supported by other models.
Motivation
Added function of OPT class, which is being actively discussed recently
Your contribution
I personally use the forSequenceCla