diff --git a/requirements/framework.txt b/requirements/framework.txt
index cc6f80636f..66ad03f7f4 100644
--- a/requirements/framework.txt
+++ b/requirements/framework.txt
@@ -32,7 +32,7 @@ sortedcontainers>=1.5.9
 tensorboard
 tiktoken
 tqdm
-transformers>=4.33,<5.8.0
+transformers>=4.33,<5.9.0
 transformers_stream_generator
 trl>=0.15,<1.0
 uvicorn
diff --git a/swift/infer_engine/transformers_engine.py b/swift/infer_engine/transformers_engine.py
index ac7e963717..6dbbe686e9 100644
--- a/swift/infer_engine/transformers_engine.py
+++ b/swift/infer_engine/transformers_engine.py
@@ -7,6 +7,7 @@
 import time
 import torch
 import torch.nn.functional as F
+from contextlib import contextmanager
 from copy import deepcopy
 from PIL import Image
 from queue import Queue
@@ -21,7 +22,7 @@
 from swift.model import get_model_processor
 from swift.template import Template
 from swift.tuners import Swift
-from swift.utils import get_last_valid_indices, safe_snapshot_download, to_device
+from swift.utils import get_last_valid_indices, safe_snapshot_download, to_device, use_hf_hub
 from .infer_engine import InferEngine
 from .protocol import (ChatCompletionResponse, ChatCompletionResponseChoice, ChatCompletionResponseStreamChoice,
                        ChatCompletionStreamResponse, ChatMessage, DeltaMessage, EmbeddingResponse,
@@ -240,7 +241,8 @@ def _infer_stream(self, inputs: Dict[str, Any], *, generation_config: Generation
         def _model_generate(**kwargs):
             if is_torch_npu_available():
                 torch.npu.set_device(self.model.device)
-            self.template.generate(self.model, **kwargs)
+            with self._patch_kernels():
+                self.template.generate(self.model, **kwargs)
 
         generate_kwargs = self.template.prepare_generate_kwargs(generate_kwargs, model=self.model)
         thread = Thread(target=_model_generate, kwargs=generate_kwargs)
@@ -384,6 +386,27 @@ def _infer_forward(self, inputs: Dict[str, Any], adapter_request: Optional[Adapt
                 res.append(ChatCompletionResponse(model=self.model_name, choices=choices, usage=usage_info))
         return res
 
+    @contextmanager
+    def _patch_kernels(self):
+        use_hf = self.use_hf if self.use_hf is not None else use_hf_hub()
+        if use_hf:
+            yield
+            return
+
+        try:
+            from modelscope import patch_hub, unpatch_hub
+        except ImportError:
+            yield
+            return
+        try:
+            patch_hub()
+        except AttributeError:
+            pass
+        try:
+            yield
+        finally:
+            unpatch_hub()
+
     def _infer_full(self, inputs: Dict[str, Any], *, generation_config: GenerationConfig,
                     adapter_request: Optional[AdapterRequest], request_config: RequestConfig,
                     template_inputs) -> List[ChatCompletionResponse]:
@@ -394,7 +417,8 @@ def _infer_full(self, inputs: Dict[str, Any], *, generation_config: GenerationCo
             generate_kwargs['adapter_names'] = adapter_names
         num_prompt_tokens = self._get_num_tokens(inputs)
         generate_kwargs = self.template.prepare_generate_kwargs(generate_kwargs, model=self.model)
-        output = dict(self.template.generate(self.model, **generate_kwargs))
+        with self._patch_kernels():
+            output = dict(self.template.generate(self.model, **generate_kwargs))
         output.pop('past_key_values', None)
         batched_generate_ids = output['sequences']
         batched_generate_ids = self.template.get_generate_ids(batched_generate_ids, num_prompt_tokens)