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update breaking change section regarding from_pretrained keyword arguments

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thomwolf
2019-07-23 15:10:02 +02:00
parent 0227b4a940
commit ba52fe69d5
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README.md
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@@ -310,8 +310,11 @@ loss, logits, attentions = outputs
### Serialization ### Serialization
Breaking change: Models are now set in evaluation mode by default when instantiated with the `from_pretrained()` method. Breaking change in the `from_pretrained()`method:
To train them don't forget to set them back in training mode (`model.train()`) to activate the dropout modules.
1. Models are now set in evaluation mode by default when instantiated with the `from_pretrained()` method. To train them don't forget to set them back in training mode (`model.train()`) to activate the dropout modules.
2. The additional `*input` and `**kwargs` arguments supplied to the `from_pretrained()` method used to be directly passed to the underlying model's class `__init__()` method. They are now used to update the model configuration attribute instead which can break derived model classes build based on the previous `BertForSequenceClassification` examples. We are working on a way to mitigate this breaking change in [#866](https://github.com/huggingface/pytorch-transformers/pull/866) by forwarding the the model `__init__()` method (i) the provided positional arguments and (ii) the keyword arguments which do not match any configuratoin class attributes.
Also, while not a breaking change, the serialization methods have been standardized and you probably should switch to the new method `save_pretrained(save_directory)` if you were using any other serialization method before. Also, while not a breaking change, the serialization methods have been standardized and you probably should switch to the new method `save_pretrained(save_directory)` if you were using any other serialization method before.