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upgrade peft, fix #1088 #1411

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hiyouga
2023-11-07 16:13:36 +08:00
parent 66a91e1fe3
commit b2a60905f3
15 changed files with 133 additions and 99 deletions
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28
src/llmtuner/tuner/core/parser.py
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@@ -132,16 +132,12 @@ def get_train_args(
if model_args.quantization_bit is not None and finetuning_args.finetuning_type != "lora":
raise ValueError("Quantization is only compatible with the LoRA method.")
if model_args.checkpoint_dir is not None:
if finetuning_args.finetuning_type != "lora" and len(model_args.checkpoint_dir) != 1:
raise ValueError("Only LoRA tuning accepts multiple checkpoints.")
if model_args.quantization_bit is not None:
if len(model_args.checkpoint_dir) != 1:
raise ValueError("Quantized model only accepts a single checkpoint. Merge them first.")
if not finetuning_args.resume_lora_training:
raise ValueError("Quantized model cannot create new LoRA weight. Merge them first.")
if (
model_args.checkpoint_dir is not None
and len(model_args.checkpoint_dir) != 1
and finetuning_args.finetuning_type != "lora"
):
raise ValueError("Only LoRA tuning accepts multiple checkpoints.")
if training_args.do_train and model_args.quantization_bit is not None and (not finetuning_args.upcast_layernorm):
logger.warning("We recommend enable `upcast_layernorm` in quantized training.")
@@ -216,11 +212,11 @@ def get_infer_args(
if model_args.quantization_bit is not None and finetuning_args.finetuning_type != "lora":
raise ValueError("Quantization is only compatible with the LoRA method.")
if model_args.checkpoint_dir is not None:
if finetuning_args.finetuning_type != "lora" and len(model_args.checkpoint_dir) != 1:
raise ValueError("Only LoRA tuning accepts multiple checkpoints.")
if model_args.quantization_bit is not None and len(model_args.checkpoint_dir) != 1:
raise ValueError("Quantized model only accepts a single checkpoint. Merge them first.")
if (
model_args.checkpoint_dir is not None
and len(model_args.checkpoint_dir) != 1
and finetuning_args.finetuning_type != "lora"
):
raise ValueError("Only LoRA tuning accepts multiple checkpoints.")
return model_args, data_args, finetuning_args, generating_args