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full finetune?

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wassname
2023-11-23 09:08:30 +08:00
parent 72ee806601
commit c3878e4a4c
1 changed files with 4 additions and 3 deletions
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src/models/transformer.py
+4 -3
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@@ -117,10 +117,11 @@ def load_pretrained_model(config, device="cuda:0"):
# tune the embedding layer and prediction head
modules_to_save = ["lm_head",], # we want the classifier parameters to be trained too when fine-tuning the base model on our custom dataset. To ensure that the classifier parameters are also trained, we specify modules_to_save.
)
base_model_peft = peft.get_peft_model(base_model, peft_config)
base_model_peft.add_adapter(adapter_name="dynamics", peft_config=peft_config) # make and set an adapter
base_model_peft = base_model
# base_model_peft = peft.get_peft_model(base_model, peft_config)
# base_model_peft.add_adapter(adapter_name="dynamics", peft_config=peft_config) # make and set an adapter
disable_causal_mask_always()
print(base_model_peft.print_trainable_parameters())
# print(base_model_peft.print_trainable_parameters())
logger.debug(f"loaded model {base_model_peft}")
return base_model_peft