[misc] lint (#9593)

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

src/llamafactory/model/model_utils/checkpointing.py

@@ -18,8 +18,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import os
 import inspect
+import os
 from functools import WRAPPER_ASSIGNMENTS, partial, wraps
 from types import MethodType
 from typing import TYPE_CHECKING, Any, Callable, Optional, Union
@@ -156,11 +156,9 @@ def prepare_model_for_training(model: "PreTrainedModel", model_args: "ModelArgum
     if (
         os.environ.get("ACCELERATE_USE_FSDP", "false").lower() == "true"
         and int(os.environ.get("FSDP_VERSION", "1")) == 2
-        ):
+    ):
         model_args.use_reentrant_gc = False
-        logger.warning_rank0(
-            "You are using fsdp2, `use_reentrant_gc` has been set to False. "
-        )
+        logger.warning_rank0("You are using fsdp2, `use_reentrant_gc` has been set to False.")
 
     if not model_args.disable_gradient_checkpointing:
         if not getattr(model, "supports_gradient_checkpointing", False):

src/llamafactory/train/sft/workflow.py

@@ -28,6 +28,7 @@ from ..trainer_utils import create_modelcard_and_push
 from .metric import ComputeAccuracy, ComputeSimilarity, eval_logit_processor
 from .trainer import CustomSeq2SeqTrainer
 
+
 if TYPE_CHECKING:
     from transformers import Seq2SeqTrainingArguments, TrainerCallback
 
@@ -144,4 +145,4 @@ def run_sft(
         trainer.save_predictions(dataset_module["eval_dataset"], predict_results, generating_args.skip_special_tokens)
 
     # Create model card
-    create_modelcard_and_push(trainer, model_args, data_args, training_args, finetuning_args)
+    create_modelcard_and_push(trainer, model_args, data_args, training_args, finetuning_args)

src/llamafactory/v1/extras/__init__.py

@@ -1 +0,0 @@
-