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@ -46,23 +46,23 @@ python -m pytest -sv tests/
This package comprises the following classes that can be imported in Python and are detailed in the [Doc](#doc) section of this readme:
- Six PyTorch models (`torch.nn.Module`) for Bert with pre-trained weights:
- `BertModel` - raw BERT Transformer model (**fully pre-trained**),
- `BertForMaskedLM` - BERT Transformer with the pre-trained masked language modeling head on top (**fully pre-trained**),
- `BertForNextSentencePrediction` - BERT Transformer with the pre-trained next sentence prediction classifier on top (**fully pre-trained**),
- `BertForPreTraining` - BERT Transformer with masked language modeling head and next sentence prediction classifier on top (**fully pre-trained**),
- `BertForSequenceClassification` - BERT Transformer with a sequence classification head on top (BERT Transformer is **pre-trained**, the sequence classification head **is only initialized and has to be trained**),
- `BertForQuestionAnswering` - BERT Transformer with a token classification head on top (BERT Transformer is **pre-trained**, the token classification head **is only initialized and has to be trained**).
- Six PyTorch models (`torch.nn.Module`) for Bert with pre-trained weights (in the [`modeling.py`](./pytorch_pretrained_bert/modeling.py) file):
- [`BertModel`](./pytorch_pretrained_bert/modeling.py#L535) - raw BERT Transformer model (**fully pre-trained**),
- [`BertForMaskedLM`](./pytorch_pretrained_bert/modeling.py#L689) - BERT Transformer with the pre-trained masked language modeling head on top (**fully pre-trained**),
- [`BertForNextSentencePrediction`](./pytorch_pretrained_bert/modeling.py#L750) - BERT Transformer with the pre-trained next sentence prediction classifier on top (**fully pre-trained**),
- [`BertForPreTraining`](./pytorch_pretrained_bert/modeling.py#L618) - BERT Transformer with masked language modeling head and next sentence prediction classifier on top (**fully pre-trained**),
- [`BertForSequenceClassification`](./pytorch_pretrained_bert/modeling.py#L812) - BERT Transformer with a sequence classification head on top (BERT Transformer is **pre-trained**, the sequence classification head **is only initialized and has to be trained**),
- [`BertForQuestionAnswering`](./pytorch_pretrained_bert/modeling.py#L877) - BERT Transformer with a token classification head on top (BERT Transformer is **pre-trained**, the token classification head **is only initialized and has to be trained**).
- Three tokenizers:
- Three tokenizers (in the [`tokenization.py`](./pytorch_pretrained_bert/tokenization.py) file):
- `BasicTokenizer` - basic tokenization (punctuation splitting, lower casing, etc.),
- `WordpieceTokenizer` - WordPiece tokenization,
- `BertTokenizer` - perform end-to-end tokenization, i.e. basic tokenization followed by WordPiece tokenization.
- One optimizer:
- One optimizer (in the [`optimization.py`](./pytorch_pretrained_bert/optimization.py) file):
- `BertAdam` - Bert version of Adam algorithm with weight decay fix, warmup and linear decay of the learning rate.
- A configuration class:
- A configuration class (in the [`modeling.py`](./pytorch_pretrained_bert/modeling.py) file):
- `BertConfig` - Configuration class to store the configuration of a `BertModel` with utilisities to read and write from JSON configuration files.
The repository further comprises: