As far as I know, there is no tool that automatically converts it, you can convert it via NumPy arrays. For example, you can convert torch.nn.Linear layer to tf.keras.layers.Dense layer with the below code.
torch_linear = ...
tf_dense = ...

kernel = torch_linear.weight.T.numpy()
bias = torch_linear.bias.numpy()
tf_dense.set_weights([kernel, bias])

Also, you can convert more complex models like BERT by converting each layer. If all operations and values are the exactly same, like the epsilon value of layer normalization(PyTorch has 1e-5 as default, and TensorFlow has 1e-3 as default), the output value will be very very close. You can check it with np.testing.assert_allclose.
I wrote a post 24 in Korean related to this topic almost a year ago.Maybe you can use the translation in Chrome or something else. You can check it if you want details.