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[Trainer
] Refactor trainer + bnb logic (#26248)
* refactor trainer + bnb logic * remove logger.info * oops
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@ -402,19 +402,23 @@ class Trainer:
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" to `True` to avoid any unexpected behavior such as device placement mismatching."
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)
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_is_peft_model = is_peft_available() and isinstance(model, PeftModel)
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_is_quantized_and_base_model = getattr(model, "is_quantized", False) and not getattr(
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model, "_hf_peft_config_loaded", False
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)
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# At this stage the model is already loaded
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if getattr(model, "is_quantized", False) and not getattr(model, "_hf_peft_config_loaded", False):
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if getattr(model, "_is_quantized_training_enabled", False):
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logger.info(
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"The model is quantized. To train this model you need to add additional modules"
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" inside the model such as adapters using `peft` library and freeze the model weights. Please"
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" check the examples in https://github.com/huggingface/peft for more details."
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)
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else:
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raise ValueError(
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"The model you want to train is loaded in 8-bit precision. if you want to fine-tune an 8-bit"
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" model, please make sure that you have installed `bitsandbytes>=0.37.0`. "
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)
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if _is_quantized_and_base_model and not _is_peft_model:
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raise ValueError(
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"You cannot perform fine-tuning on purely quantized models. Please attach trainable adapters on top of"
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" the quantized model to correctly perform fine-tuning. Please see: https://huggingface.co/docs/transformers/peft"
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" for more details"
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)
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elif _is_quantized_and_base_model and not getattr(model, "_is_quantized_training_enabled", False):
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raise ValueError(
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"The model you want to train is loaded in 8-bit precision. if you want to fine-tune an 8-bit"
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" model, please make sure that you have installed `bitsandbytes>=0.37.0`. "
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)
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# Setup Sharded DDP training
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self.sharded_ddp = None
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