🚀 Add missing tokenizer test files

Several tokenizers currently have no associated tests. I think that adding the test file for one of these tokenizers could be a very good way to make a first contribution to transformers.

Tokenizers concerned

not yet claimed

none

claimed

• LED @nnlnr
• Flaubert @anmolsjoshi
• Longformer @tgadeliya
• Electra @rajathb

It would be great if you could add the JAX equivalent of scipy.stats.mode, which is currently unavailable.

A use case may be a ML classification task with ensembles, where multiple models give different predictions, and we are interested in finding the most common one.

As an example, consider predictions to be a two-dimensional DeviceArray of predictions, with
shape = (number of model

Is there a way to train a bidirectional RNN (like LSTM or GRU) on trax nowadays?

Love the book! Ran into this display issue when viewing it on Chrome's PDF viewer:

Dear Numpyro developers,

Please develop Euler Maruyama features in numpyro similar to features found in PyMC.

Thanks alot.

Dear Brax team,

Since Brax is fully differentiable, I thought it'd be possible to use it like DiffTaichi or GradSim for system identification (e.g. determining the mass of an object from a trajectory and known force) but I couldn't find any example for this.
Do you happen to have any demo or tips for this?

From the top of my head I would do something like this:
Let's say the task is to es

these are the examples on docs/notebooks/

Probably it's necessary to add this line when running on TPUs https://github.com/google/jax#pip-installation-colab-tpu

I think this would be a good first issue