Use return_tensors="np" instead of "tf"
This PR is doing exactly the same thing as the [notebooks PR here](https://github.com/huggingface/notebooks/pull/308).

In our TF examples, we use return_tensors="tf" for the data collators. However, `prepare_tf_dataset` and `to_tf_dataset` actually use a NumPy loader internally, which we wrap with a `tf.data.Dataset` at the end. As a result, return_tensors="np" works much better for them, and avoids some weird slowdown bugs we've experienced.

This PR replaces every instance in our examples with return_tensors="np". (cc @gante, @amyeroberts, @sayakpaul just so you're aware)

_The documentation is not available anymore as the PR was closed or merged._