diff --git a/modelscope/hub/constants.py b/modelscope/hub/constants.py
index fb8bd5f5..93d6ae84 100644
--- a/modelscope/hub/constants.py
+++ b/modelscope/hub/constants.py
@@ -19,7 +19,7 @@ REQUESTS_API_HTTP_METHOD = ['get', 'head', 'post', 'put', 'patch', 'delete']
 API_HTTP_CLIENT_TIMEOUT = 60
 API_RESPONSE_FIELD_DATA = 'Data'
 API_FILE_DOWNLOAD_RETRY_TIMES = 5
-API_FILE_DOWNLOAD_TIMEOUT = 60 * 5
+API_FILE_DOWNLOAD_TIMEOUT = 30
 API_FILE_DOWNLOAD_CHUNK_SIZE = 1024 * 1024 * 16
 API_RESPONSE_FIELD_GIT_ACCESS_TOKEN = 'AccessToken'
 API_RESPONSE_FIELD_USERNAME = 'Username'
diff --git a/modelscope/hub/file_download.py b/modelscope/hub/file_download.py
index cb95e164..f2ec1127 100644
--- a/modelscope/hub/file_download.py
+++ b/modelscope/hub/file_download.py
@@ -187,23 +187,36 @@ def get_file_download_url(model_id: str, file_path: str, revision: str):
     )
 
 
-def download_part(params):
+def download_part_with_retry(params):
     # unpack parameters
     progress, start, end, url, file_name, cookies, headers = params
     get_headers = {} if headers is None else copy.deepcopy(headers)
     get_headers['Range'] = 'bytes=%s-%s' % (start, end)
-    with open(file_name, 'rb+') as f:
-        f.seek(start)
-        r = requests.get(
-            url,
-            stream=True,
-            headers=get_headers,
-            cookies=cookies,
-            timeout=API_FILE_DOWNLOAD_TIMEOUT)
-        for chunk in r.iter_content(chunk_size=API_FILE_DOWNLOAD_CHUNK_SIZE):
-            if chunk:  # filter out keep-alive new chunks
-                f.write(chunk)
-                progress.update(len(chunk))
+    retry = Retry(
+        total=API_FILE_DOWNLOAD_RETRY_TIMES,
+        backoff_factor=1,
+        allowed_methods=['GET'])
+    while True:
+        try:
+            with open(file_name, 'rb+') as f:
+                f.seek(start)
+                r = requests.get(
+                    url,
+                    stream=True,
+                    headers=get_headers,
+                    cookies=cookies,
+                    timeout=API_FILE_DOWNLOAD_TIMEOUT)
+                for chunk in r.iter_content(
+                        chunk_size=API_FILE_DOWNLOAD_CHUNK_SIZE):
+                    if chunk:  # filter out keep-alive new chunks
+                        f.write(chunk)
+            progress.update(end - start)
+            break
+        except (Exception) as e:  # no matter what exception, we will retry.
+            retry = retry.increment('GET', url, error=e)
+            logger.warning('Download file from: %s to: %s failed, will retry' %
+                           (start, end))
+            retry.sleep()
 
 
 def parallel_download(
@@ -226,7 +239,7 @@ def parallel_download(
             initial=0,
             desc='Downloading',
         )
-        PART_SIZE = 160 * 1024 * 1012  # every part is 160M
+        PART_SIZE = 160 * 1024 * 1024  # every part is 160M
         tasks = []
         for idx in range(int(file_size / PART_SIZE)):
             start = idx * PART_SIZE
@@ -240,7 +253,7 @@ def parallel_download(
         with ThreadPoolExecutor(
                 max_workers=parallels,
                 thread_name_prefix='download') as executor:
-            list(executor.map(download_part, tasks))
+            list(executor.map(download_part_with_retry, tasks))
 
         progress.close()
 
diff --git a/modelscope/utils/automodel_utils.py b/modelscope/utils/automodel_utils.py
index 56075618..afd83817 100644
--- a/modelscope/utils/automodel_utils.py
+++ b/modelscope/utils/automodel_utils.py
@@ -66,7 +66,7 @@ def try_to_load_hf_model(model_dir: str, task_name: str,
 
     if use_hf and automodel_class is None:
         raise ValueError(f'Model import failed. You used `use_hf={use_hf}`, '
-                         'but the model is not a model of hf')
+                         'but the model is not a model of hf.')
 
     model = None
     if automodel_class is not None:
diff --git a/modelscope/utils/hf_util.py b/modelscope/utils/hf_util.py
index 2a534eb6..fd367847 100644
--- a/modelscope/utils/hf_util.py
+++ b/modelscope/utils/hf_util.py
@@ -112,22 +112,29 @@ def check_hf_code(model_dir: str, auto_class: type,
     # trust_remote_code is False or has_remote_code is False
     model_type = config_dict.get('model_type', None)
     if model_type is None:
-        raise ValueError(f'`model_type` key is not found in {config_path}')
+        raise ValueError(f'`model_type` key is not found in {config_path}.')
 
+    trust_remote_code_info = '.'
+    if not trust_remote_code:
+        trust_remote_code_info = ', You can try passing `trust_remote_code=True`.'
     if auto_class is AutoConfigHF:
         if model_type not in CONFIG_MAPPING:
-            raise ValueError(f'{model_type} not found in HF CONFIG_MAPPING')
+            raise ValueError(
+                f'{model_type} not found in HF `CONFIG_MAPPING`{trust_remote_code_info}'
+            )
     elif auto_class is AutoTokenizerHF:
         if model_type not in TOKENIZER_MAPPING_NAMES:
             raise ValueError(
-                f'{model_type} not found in HF TOKENIZER_MAPPING_NAMES')
+                f'{model_type} not found in HF `TOKENIZER_MAPPING_NAMES`{trust_remote_code_info}'
+            )
     else:
         mapping_names = [
             m.model_type for m in auto_class._model_mapping.keys()
         ]
         if model_type not in mapping_names:
             raise ValueError(
-                f'{model_type} not found in HF auto_class._model_mapping')
+                f'{model_type} not found in HF `auto_class._model_mapping`{trust_remote_code_info}'
+            )
 
 
 def get_wrapped_class(module_class, ignore_file_pattern=[], **kwargs):