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use new shared.args.lora_dir
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@ -92,8 +92,7 @@ def do_train(lora_name: str, micro_batch_size: int, batch_size: int, epochs: int
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# == Input validation / processing ==
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yield "Prepping..."
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# TODO: --lora-dir PR once pulled will need to be applied here
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lora_name = f"loras/{clean_path(None, lora_name)}"
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lora_name = f"{shared.args.lora_dir}/{clean_path(None, lora_name)}"
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if dataset is None:
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return "**Missing dataset choice input, cannot continue.**"
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if format is None:
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