From 7c91e51c26671898119e60236e9a496f99bcc652 Mon Sep 17 00:00:00 2001 From: Thomas Wolf Date: Sat, 17 Nov 2018 22:54:15 +0100 Subject: [PATCH] update links in readme --- README.md | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 552991c907..d7e9d1f705 100644 --- a/README.md +++ b/README.md @@ -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: