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![]() * pytorch examples
* pytorch mim no trainer
* cookiecutter
* flax examples
* missed line in pytorch run_glue
* tensorflow examples
* tensorflow run_clip
* tensorflow run_mlm
* tensorflow run_ner
* tensorflow run_clm
* pytorch example from_configs
* pytorch no trainer examples
* Revert "tensorflow run_clip"
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README.md | ||
requirements.txt | ||
run_summarization.py |
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