Hi,
I would like to use a model built using PyTorch (namely this one ) in a Tensorflow environment.
More specifically I would like to start by just extract some of the embeddings in the later layers, and then potentially run some fine-tuning.
So I have two questions:
- Is there a way to load and run inference from a PyTorch model in TensorFlow?
- Is there a way to load and fine-tune a PyTorch model in Tensorflow?
Thanks in advance!
lewtun
2
Hi @gruffgoran, your use cases sound like a perfect match for the ONNX format
Having said that, you might be able to get a quick win by trying something like the following (see docs):
tf_model = TFBertForSequenceClassification.from_pretrained("KB/bert-base-swedish-cased", from_pt=True)
From here you can then run inference / fine-tune etc using TensorFlow.
If you want to go the ONNX route, the idea would be to convert PyTorch → ONNX and then load the ONNX model in TensorFlow. Details on doing the conversion can be found here: Exporting transformers models — transformers 4.3.0 documentation
Hello, thanks but the link seems to be broken: https://huggingface.co/transformers/serialization.html#onnx-onnxruntime
Please direct to the correct one.