diff --git a/README.md b/README.md
index 799c5019..ad9ff286 100644
--- a/README.md
+++ b/README.md
@@ -87,6 +87,7 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
 </details>
 
 ## Changelog
+
 [25/01/15] We supported fine-tuning the **[InternLM3](https://huggingface.co/collections/internlm/)** models. Thank [@hhaAndroid](https://github.com/hhaAndroid)'s PR.
 
 [25/01/10] We supported fine-tuning the **[Phi-4](https://huggingface.co/microsoft/phi-4)** model.
diff --git a/src/llamafactory/chat/hf_engine.py b/src/llamafactory/chat/hf_engine.py
index 6f61f2ab..c2e3e114 100644
--- a/src/llamafactory/chat/hf_engine.py
+++ b/src/llamafactory/chat/hf_engine.py
@@ -169,7 +169,7 @@ class HuggingfaceEngine(BaseEngine):
             if isinstance(value, list) and all(isinstance(v, torch.Tensor) for v in value):  # for pixtral inputs
                 value = torch.stack(value)  # assume they have same sizes
             elif isinstance(value, list) and all(isinstance(v, list) for v in value):  # for minicpmv inputs
-                value = torch.stack([torch.stack(per_value) for per_value in value])
+                value = torch.stack([torch.stack(v) for v in value])
             elif not isinstance(value, torch.Tensor):
                 value = torch.tensor(value)
 
@@ -215,7 +215,7 @@ class HuggingfaceEngine(BaseEngine):
         )
         generate_output = model.generate(**gen_kwargs)
         if isinstance(generate_output, tuple):
-            generate_output = generate_output[1][0]  # for minicpm_o
+            generate_output = generate_output[1][0]  # post-process the minicpm_o output
 
         response_ids = generate_output[:, prompt_length:]
         response = tokenizer.batch_decode(
diff --git a/src/llamafactory/data/template.py b/src/llamafactory/data/template.py
index 07be3cec..4d7f5eb9 100644
--- a/src/llamafactory/data/template.py
+++ b/src/llamafactory/data/template.py
@@ -732,15 +732,18 @@ _register_template(
     stop_words=["<|im_end|>"],
 )
 
+
+# copied from intern2 template
 _register_template(
     name="intern3",
     format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
     format_assistant=StringFormatter(slots=["{{content}}<|im_end|>\n"]),
     format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
     format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
-    stop_words=["<|im_end|>"]
+    stop_words=["<|im_end|>"],
 )
 
+
 _register_template(
     name="llama2",
     format_user=StringFormatter(slots=[{"bos_token"}, "[INST] {{content}} [/INST]"]),
diff --git a/src/llamafactory/model/loader.py b/src/llamafactory/model/loader.py
index 4d6b5a99..b450e72d 100644
--- a/src/llamafactory/model/loader.py
+++ b/src/llamafactory/model/loader.py
@@ -85,7 +85,7 @@ def load_tokenizer(model_args: "ModelArguments") -> "TokenizerModule":
         )
     except Exception as e:
         raise OSError("Failed to load tokenizer.") from e
-        
+
     if model_args.model_max_length is not None and tokenizer.model_max_length != model_args.model_max_length:
         tokenizer.model_max_length = model_args.model_max_length
 
diff --git a/src/llamafactory/model/patcher.py b/src/llamafactory/model/patcher.py
index 4dc7e1b5..c33527a6 100644
--- a/src/llamafactory/model/patcher.py
+++ b/src/llamafactory/model/patcher.py
@@ -110,7 +110,7 @@ def patch_config(
 
     if getattr(config, "model_type", None) == "qwen2" and is_trainable and model_args.flash_attn == "fa2":
         setattr(config, "use_cache", False)  # qwen2 does not support use_cache when using flash attn
-    
+
     if getattr(config, "model_type", None) == "minicpmo":
         setattr(config, "init_audio", False)
         setattr(config, "init_tts", False)
@@ -119,7 +119,7 @@ def patch_config(
         raise ValueError("Please download llava models with hf-compatible format: https://huggingface.co/llava-hf")
 
     if getattr(config, "model_type", None) == "internlm3" and not is_transformers_version_greater_than("4.47.1"):
-        raise RuntimeError("InternLM3 model requires transformers >= 4.47.1, please upgrade it.")
+        raise RuntimeError("InternLM3 model requires transformers>=4.47.1, please upgrade it.")
 
     # deepspeed zero3 is not compatible with low_cpu_mem_usage
     init_kwargs["low_cpu_mem_usage"] = model_args.low_cpu_mem_usage and (not is_deepspeed_zero3_enabled())
@@ -153,7 +153,7 @@ def patch_model(
     ):
         gen_config.do_sample = True
 
-    if getattr(model.config, "model_type") not in ["minicpmv", "minicpmo"] and "GenerationMixin" not in str(
+    if getattr(model.config, "model_type", None) not in ["minicpmv", "minicpmo"] and "GenerationMixin" not in str(
         model.generate.__func__
     ):
         model.generate = MethodType(PreTrainedModel.generate, model)