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# 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 | |
``` |