bert

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

Describe the bug

• Currently users can pass any model type to FARMReader, but passing an unsupported one (not BERT-based) will cause obscure crashes.

Expected behavior

• FARMReader should reject the wrong model with a clear error message explaining what's the issue.
• The error message might even suggesting a valid model instead.

To Reproduce

• Try to load a pipeline with

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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

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.