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Swap TF and PT code inside two blocks (#14742)

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Lucien
2021-12-13 23:31:11 +08:00
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parent 8362d07d63
commit fc74c84537
1 changed files with 6 additions and 6 deletions
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docs/source/quicktour.mdx
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@@ -334,21 +334,21 @@ PyTorch and TensorFlow: any model saved as before can be loaded back either in P
If you would like to load your saved model in the other framework, first make sure it is installed: If you would like to load your saved model in the other framework, first make sure it is installed:
```bash ```bash
pip install tensorflow
===PT-TF-SPLIT===
pip install torch pip install torch
===PT-TF-SPLIT===
pip install tensorflow
``` ```
Then, use the corresponding Auto class to load it like this: Then, use the corresponding Auto class to load it like this:
```py ```py
>>> from transformers import TFAutoModel
>>> tokenizer = AutoTokenizer.from_pretrained(pt_save_directory)
>>> tf_model = TFAutoModel.from_pretrained(pt_save_directory, from_pt=True)
===PT-TF-SPLIT===
>>> from transformers import AutoModel >>> from transformers import AutoModel
>>> tokenizer = AutoTokenizer.from_pretrained(tf_save_directory) >>> tokenizer = AutoTokenizer.from_pretrained(tf_save_directory)
>>> pt_model = AutoModel.from_pretrained(tf_save_directory, from_tf=True) >>> pt_model = AutoModel.from_pretrained(tf_save_directory, from_tf=True)
===PT-TF-SPLIT===
>>> from transformers import TFAutoModel
>>> tokenizer = AutoTokenizer.from_pretrained(pt_save_directory)
>>> tf_model = TFAutoModel.from_pretrained(pt_save_directory, from_pt=True)
``` ```
Lastly, you can also ask the model to return all hidden states and all attention weights if you need them: Lastly, you can also ask the model to return all hidden states and all attention weights if you need them: