Can I train question-answering on TPU using Huggingface
# ❓ Questions & Help
I am trying to run run_squad from question answering on TPU but I get the following error.

## Details
export SQUAD_DIR=/path/to/SQUAD
python examples/xla_spawn.py --num_cores 8 \
 run_squad.py \
  --model_type bert \
  --model_name_or_path bert-base-uncased \
  --do_train \
  --do_eval \
  --do_lower_case \
  --train_file $SQUAD_DIR/train-v1.1.json \
  --predict_file $SQUAD_DIR/dev-v1.1.json \
  --per_gpu_train_batch_size 12 \
  --learning_rate 3e-5 \
  --num_train_epochs 2.0 \
  --max_seq_length 384 \
  --doc_stride 128 \
  --output_dir /tmp/debug_squad/

**run_squad.py: error: unrecognized arguments: --tpu_num_cores 1**



as you can see in https://github.com/huggingface/transformers/tree/master/examples#the-big-table-of-tasks `question-answering` is not implemented using Trainer, yet – so doesn't have TPU support. 

This is on our todo-list but might take a few weeks. Feel free to open a PR though – or use TFTrainer is TF is an option<|||||>I think I can live with TFTrainer ... Thanks for the reply<|||||>how do i use TFTrainer with TPU<|||||>Hi! The [running on TPU](https://github.com/huggingface/transformers/tree/master/examples#running-on-tpus) section of the examples covers that.

Basically, if on a correctly setup TPU, the TF trainer will automatically launch on TPU.