diff --git a/examples/accelerate/fsdp2_config.yaml b/examples/accelerate/fsdp2_config.yaml
new file mode 100644
index 00000000..5ea46683
--- /dev/null
+++ b/examples/accelerate/fsdp2_config.yaml
@@ -0,0 +1,22 @@
+compute_environment: LOCAL_MACHINE
+debug: false
+distributed_type: FSDP
+downcast_bf16: 'no'
+fsdp_config:
+  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  fsdp_cpu_ram_efficient_loading: true
+  fsdp_offload_params: false
+  fsdp_reshard_after_forward: true
+  fsdp_state_dict_type: FULL_STATE_DICT
+  fsdp_version: 2
+machine_rank: 0
+main_training_function: main
+mixed_precision: bf16  # or fp16
+num_machines: 1  # the number of nodes
+num_processes: 2  # the number of GPUs in all nodes
+rdzv_backend: static
+same_network: true
+tpu_env: []
+tpu_use_cluster: false
+tpu_use_sudo: false
+use_cpu: false
\ No newline at end of file
diff --git a/src/llamafactory/model/model_utils/checkpointing.py b/src/llamafactory/model/model_utils/checkpointing.py
index 714aca03..bdd06e7d 100644
--- a/src/llamafactory/model/model_utils/checkpointing.py
+++ b/src/llamafactory/model/model_utils/checkpointing.py
@@ -18,6 +18,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
 import inspect
 from functools import WRAPPER_ASSIGNMENTS, partial, wraps
 from types import MethodType
@@ -152,6 +153,15 @@ def prepare_model_for_training(model: "PreTrainedModel", model_args: "ModelArgum
             if param.ndim == 1 and any(ln_name in name for ln_name in LAYERNORM_NAMES):
                 param.data = param.data.to(torch.float32)
 
+    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. "
+        )
+
     if not model_args.disable_gradient_checkpointing:
         if not getattr(model, "supports_gradient_checkpointing", False):
             logger.warning_rank0("Current model does not support gradient checkpointing.")