fix link in readme
This commit is contained in:
parent
6b2136a8a9
commit
60e01ac427
|
@ -483,7 +483,7 @@ Please follow the instructions given in the notebooks to run and modify them.
|
|||
|
||||
A command-line interface is provided to convert a TensorFlow checkpoint in a PyTorch dump of the `BertForPreTraining` class (see above).
|
||||
|
||||
You can convert any TensorFlow checkpoint for BERT (in particular [the pre-trained models released by Google](https://github.com/google-research/bert#pre-trained-models)) in a PyTorch save file by using the [`convert_tf_checkpoint_to_pytorch.py`](convert_tf_checkpoint_to_pytorch.py) script.
|
||||
You can convert any TensorFlow checkpoint for BERT (in particular [the pre-trained models released by Google](https://github.com/google-research/bert#pre-trained-models)) in a PyTorch save file by using the [`./pytorch_pretrained_bert/convert_tf_checkpoint_to_pytorch.py`](convert_tf_checkpoint_to_pytorch.py) script.
|
||||
|
||||
This CLI takes as input a TensorFlow checkpoint (three files starting with `bert_model.ckpt`) and the associated configuration file (`bert_config.json`), and creates a PyTorch model for this configuration, loads the weights from the TensorFlow checkpoint in the PyTorch model and saves the resulting model in a standard PyTorch save file that can be imported using `torch.load()` (see examples in `extract_features.py`, `run_classifier.py` and `run_squad.py`).
|
||||
|
||||
|
|
Loading…
Reference in New Issue