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improve aligner

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hiyouga
2024-02-10 16:39:19 +08:00
parent 388b705a8d
commit 7d2dc83c5e
11 changed files with 127 additions and 112 deletions
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10
src/llmtuner/hparams/parser.py
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@@ -67,7 +67,7 @@ def _verify_model_args(model_args: "ModelArguments", finetuning_args: "Finetunin
raise ValueError("Quantized model only accepts a single adapter. Merge them first.")
if model_args.adapter_name_or_path is not None and finetuning_args.finetuning_type != "lora":
raise ValueError("Only LoRA method has adapters.")
raise ValueError("Adapter is only valid for the LoRA method.")
def _parse_train_args(args: Optional[Dict[str, Any]] = None) -> _TRAIN_CLS:
@@ -125,6 +125,14 @@ def get_train_args(args: Optional[Dict[str, Any]] = None) -> _TRAIN_CLS:
_verify_model_args(model_args, finetuning_args)
if (
training_args.do_train
and finetuning_args.finetuning_type == "lora"
and model_args.resize_vocab
and finetuning_args.additional_target is None
):
logger.warning("Add token embeddings to `additional_target` to make the added tokens trainable.")
if training_args.do_train and model_args.quantization_bit is not None and (not model_args.upcast_layernorm):
logger.warning("We recommend enable `upcast_layernorm` in quantized training.")