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Training_PRO fix: add if 'quantization_config' in shared.model.config.to_dict()

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FP HAM 2025-01-08 14:54:09 -05:00 committed by GitHub
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commit 03a0f236a4
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1 changed files with 5 additions and 1 deletions
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extensions/Training_PRO/script.py
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@ -789,7 +789,11 @@ def do_train(lora_name: str, always_override: bool, save_steps: int, micro_batch
if not hasattr(shared.model, 'lm_head') or hasattr(shared.model.lm_head, 'weight'):
logger.info("Getting model ready...")
# here we can disable gradient checkpoint, by default = true, use_gradient_checkpointing=True
prepare_model_for_kbit_training(shared.model)
if 'quantization_config' in shared.model.config.to_dict():
print(f"Method: {RED}QLORA{RESET}")
prepare_model_for_kbit_training(shared.model)
else:
print(f"Method: {RED}LoRA{RESET}")
# base model is now frozen and should not be reused for any other LoRA training than this one
shared.model_dirty_from_training = True