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transformers/examples/tensorflow/summarization
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Sylvain Gugger 4975002df5
Reorganize file utils (#16264) 
* Split file_utils in several submodules

* Fixes

* Add back more objects

* More fixes

* Who exactly decided to import that from there?

* Second suggestion to code with code review

* Revert wront move

* Fix imports

* Adapt all imports

* Adapt all imports everywhere

* Revert this import, will fix in a separate commit
2022-03-23 10:26:33 -04:00
..
README.md TF summarization example (#12617) 2021-07-12 15:58:38 +01:00
run_summarization.py Reorganize file utils (#16264) 2022-03-23 10:26:33 -04:00

README.md

Summarization example

This script shows an example of training a summarization model with the 🤗 Transformers library. For straightforward use-cases you may be able to use these scripts without modification, although we have also included comments in the code to indicate areas that you may need to adapt to your own projects.

Multi-GPU and TPU usage

By default, these scripts use 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.

Example command

python run_summarization.py  \
--model_name_or_path facebook/bart-base \
--dataset_name cnn_dailymail \
--dataset_config "3.0.0" \
--output_dir /tmp/tst-summarization  \
--per_device_train_batch_size 8 \
--per_device_eval_batch_size 16 \
--num_train_epochs 3 \
--do_train \
--do_eval