Add TF contrastive image text finetuning example
This PR adds a TF port of the PyTorch example for finetuning the `TFVisionTextDualEncoderModel` class. Functionality is largely the same, but I used a `tf.data` pipeline to efficiently stream images instead of `torchvision`. I also added the ability to specify separate image/text models with arguments, whereas in the PyTorch example you have to create the dual encoder with a separate script.

I also caught a small bug in the original model code while writing this - loss is a scalar rather than having shape `(1,)`. That's fixed in here too!
_The documentation is not available anymore as the PR was closed or merged._<|||||>Update: Woah! The argument names to `PushToHubCallback` across our examples became outdated and tests weren't picking that up. I'm fixing it in this PR too.