Below is an example of how to use the training scripts for adapter tuning. The TRAIN_FILEs (and VALIDATION_FILEs) follow the same format as SFT:
python /opt/NeMo/examples/nlp/language_modeling/tuning/megatron_t5_finetuning.py \
model.language_model_path=<BASE_T5_MODEL> \
model.data.train_ds=[<TRAIN_FILE1>,<TRAIN_FILE2>,...] \
model.data.validation_ds=[<VALIDATION_FILE1>, <VALIDATION_FILE2>,...]
At the end of tuning, a ‘.nemo’ model is generated which contains the parameters for the PEFT model. Similarly, the PEFT framework has an inference script as well:
python /opt/NeMo/examples/nlp/language_modeling/tuning/megatron_t5_generate.py \
data.test_ds=[<TEST_FILE>] \
language_model_path=[BASE_T5_MODEL] \
adapter_model_file=[PEFT_MODEL] \
pred_file_path=<OUTPUT_FILE>