diff --git a/trl/models/modeling_base.py b/trl/models/modeling_base.py
index b675420d0e..7cd85678d1 100644
--- a/trl/models/modeling_base.py
+++ b/trl/models/modeling_base.py
@@ -20,6 +20,7 @@
 import torch.nn as nn
 from accelerate import Accelerator
 from huggingface_hub import hf_hub_download
+from huggingface_hub.utils import EntryNotFoundError, HFValidationError, LocalEntryNotFoundError
 from transformers import PreTrainedModel
 
 from ..import_utils import is_peft_available
@@ -163,7 +164,7 @@ class and the arguments that are specific to trl models. The kwargs
                         "adapter_config.json",
                         token=token,
                     )
-                except:  # noqa
+                except (EntryNotFoundError, LocalEntryNotFoundError, HFValidationError):
                     remote_adapter_config = None
             else:
                 remote_adapter_config = None
@@ -181,7 +182,8 @@ class and the arguments that are specific to trl models. The kwargs
                 if local_adapter_present:
                     trained_adapter_config = PeftConfig.from_pretrained(pretrained_model_name_or_path)
                 else:
-                    trained_adapter_config = PeftConfig.from_pretrained(remote_adapter_config)
+                    remote_adapter_dir = os.path.dirname(remote_adapter_config)
+                    trained_adapter_config = PeftConfig.from_pretrained(remote_adapter_dir)
 
                 # Load the pretrained base model
                 pretrained_model = cls.transformers_parent_class.from_pretrained(
@@ -253,7 +255,7 @@ class and the arguments that are specific to trl models. The kwargs
                         token=token,
                     )
                 # sharded
-                except:  # noqa
+                except (EntryNotFoundError, LocalEntryNotFoundError, HFValidationError):
                     if os.path.exists(sharded_index_filename):
                         index_file_name = sharded_index_filename
                     else:
@@ -263,7 +265,8 @@ class and the arguments that are specific to trl models. The kwargs
                                 "pytorch_model.bin.index.json",
                                 token=token,
                             )
-                        except ValueError:  # not continue training, do not have v_head weight
+                        except (EntryNotFoundError, LocalEntryNotFoundError, HFValidationError):
+                            # not continue training, do not have v_head weight
                             is_resuming_training = False
                             logging.warning(
                                 f"A {type(pretrained_model)} model is loaded from '{pretrained_model_name_or_path}', "
@@ -279,6 +282,7 @@ class and the arguments that are specific to trl models. The kwargs
                             if any([module in k for module in cls.supported_modules]):
                                 files_to_download.add(v)
                         is_shared = True
+
             if is_resuming_training:
                 if is_shared:
                     # download each file and add it to the state_dict