fixed flake8 lint issues

convert_hf_to_gguf.py

@@ -6005,6 +6005,7 @@ class Gemma3VisionModel(MmprojModel):
 
         return [] # skip other tensors
 
+
 @ModelBase.register("DeepseekOCRForCausalLM")
 class DeepseekOCRVisionModel(MmprojModel):
     def set_gguf_parameters(self):
@@ -6044,7 +6045,6 @@ class DeepseekOCRVisionModel(MmprojModel):
 
         return vision_config
 
-
     def tensor_force_quant(self, name, new_name, bid, n_dims):
         # TODO: increase numercial stability. maybe delete later.
         return gguf.GGMLQuantizationType.F32
@@ -7354,8 +7354,12 @@ class DeepseekV2Model(TextModel):
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         # skip vision tensors and remove "language_model." for Kimi-VL
-        if "vision_" in name or "multi_modal_projector" in name \
-            or "image_newline" in name or "model.projector" in name or "sam_model" in name or "view_seperator" in name:
+        if ("vision_" in name
+                or "multi_modal_projector" in name
+                or "image_newline" in name
+                or "model.projector" in name
+                or "sam_model" in name
+                or "view_seperator" in name):
             return []
 
         if name.startswith("language_model."):
@@ -7435,6 +7439,7 @@ class DeepseekV2Model(TextModel):
             if len(experts) > 0:
                 raise ValueError(f"Unprocessed experts: {experts}")
 
+
 @ModelBase.register("MiniMaxM2ForCausalLM")
 class MiniMaxM2Model(TextModel):
     model_arch = gguf.MODEL_ARCH.MINIMAXM2