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fix inference

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Former-commit-id: d3a0692d4d9033a3b58d68357294854144479536
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hiyouga 2023-08-01 00:06:48 +08:00
parent d5d3b2a42f
commit e34fc5fd2e
2 changed files with 3 additions and 2 deletions
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3
src/llmtuner/tuner/core/loader.py
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@ -18,10 +18,11 @@ from trl import AutoModelForCausalLMWithValueHead
from llmtuner.extras.logging import get_logger from llmtuner.extras.logging import get_logger
from llmtuner.extras.misc import count_parameters, prepare_model_for_training from llmtuner.extras.misc import count_parameters, prepare_model_for_training
from llmtuner.extras.save_and_load import load_valuehead_params from llmtuner.extras.save_and_load import load_valuehead_params
from llmtuner.hparams import FinetuningArguments
from llmtuner.tuner.core.adapter import init_adapter from llmtuner.tuner.core.adapter import init_adapter
if TYPE_CHECKING: if TYPE_CHECKING:
from llmtuner.hparams import ModelArguments, FinetuningArguments from llmtuner.hparams import ModelArguments
logger = get_logger(__name__) logger = get_logger(__name__)

2
src/llmtuner/tuner/core/trainer.py
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@ -68,7 +68,7 @@ class PeftTrainer(Seq2SeqTrainer):
else: else:
torch.save(state_dict, os.path.join(output_dir, WEIGHTS_NAME)) torch.save(state_dict, os.path.join(output_dir, WEIGHTS_NAME))
if self.tokenizer is not None: if self.finetuning_args.finetuning_type == "full" and self.tokenizer is not None:
self.tokenizer.save_pretrained(output_dir) self.tokenizer.save_pretrained(output_dir)
with open(os.path.join(output_dir, TRAINING_ARGS_NAME), "w", encoding="utf-8") as f: with open(os.path.join(output_dir, TRAINING_ARGS_NAME), "w", encoding="utf-8") as f: