Tensorflow QA example (#12252)

* New Tensorflow QA example!

* Style pass

* Updating README.md for the new example

* flake8 fixes

* Update examples/tensorflow/question-answering/README.md

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

examples/tensorflow/question-answering/README.md

@@ -1,5 +1,5 @@
 <!---
-Copyright 2020 The HuggingFace Team. All rights reserved.
+Copyright 2021 The HuggingFace Team. All rights reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -14,21 +14,42 @@ See the License for the specific language governing permissions and
 limitations under the License.
 -->
 
-## SQuAD with the Tensorflow Trainer
+# Question answering example
 
-```bash
-python run_tf_squad.py \
-    --model_name_or_path bert-base-uncased \
-    --output_dir model \
-    --max_seq_length 384 \
-    --num_train_epochs 2 \
-    --per_gpu_train_batch_size 8 \
-    --per_gpu_eval_batch_size 16 \
-    --do_train \
-    --logging_dir logs \    
-    --logging_steps 10 \
-    --learning_rate 3e-5 \
-    --doc_stride 128    
+This folder contains the `run_qa.py` script, demonstrating *question answering* with the 🤗 Transformers library.
+For straightforward use-cases you may be able to use this script without modification, although we have also
+included comments in the code to indicate areas that you may need to adapt to your own projects. 
+
+### Usage notes
+Note that when contexts are long they may be split into multiple training cases, not all of which may contain
+the answer span. 
+
+As-is, the example script will train on SQuAD or any other question-answering dataset formatted the same way, and can handle user
+inputs as well.
+
+### Multi-GPU and TPU usage
+
+By default, the script uses a `MirroredStrategy` and will use multiple GPUs effectively if they are available. TPUs
+can also be used by passing the name of the TPU resource with the `--tpu` argument. There are some issues surrounding
+these strategies and our models right now, which are most likely to appear in the evaluation/prediction steps. We're
+actively working on better support for multi-GPU and TPU training in TF, but if you encounter problems a quick 
+workaround is to train in the multi-GPU or TPU context and then perform predictions outside of it.
+
+### Memory usage and data loading
+
+One thing to note is that all data is loaded into memory in this script. Most question answering datasets are small
+enough that this is not an issue, but if you have a very large dataset you will need to modify the script to handle
+data streaming. This is particularly challenging for TPUs, given the stricter requirements and the sheer volume of data
+required to keep them fed. A full explanation of all the possible pitfalls is a bit beyond this example script and 
+README, but for more information you can see the 'Input Datasets' section of 
+[this document](https://www.tensorflow.org/guide/tpu).
+
+### Example command
+```
+python run_qa.py \
+--model_name_or_path distilbert-base-cased \
+--output_dir output \
+--dataset_name squad \
+--do_train \
+--do_eval \
 ```
-
-For the moment evaluation is not available in the Tensorflow Trainer only the training.