diff --git a/examples/llava/README-glmedge.md b/examples/llava/README-glmedge.md
index c36203c9e..603d01474 100644
--- a/examples/llava/README-glmedge.md
+++ b/examples/llava/README-glmedge.md
@@ -37,7 +37,7 @@ python ./examples/llava/glmedge-convert-image-encoder-to-gguf.py -m ../model_pat
 5. Use `examples/convert_hf_to_gguf.py` to convert the LLM part of GLMV-EDGE to GGUF:
 
 ```sh
-python convert_hf_to_gguf.py ../model_path 
+python convert_hf_to_gguf.py ../model_path
 ```
 
-Now both the LLM part and the image encoder are in the `model_path` directory.
\ No newline at end of file
+Now both the LLM part and the image encoder are in the `model_path` directory.
diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp
index 75c170520..931cc406b 100644
--- a/examples/llava/clip.cpp
+++ b/examples/llava/clip.cpp
@@ -2720,4 +2720,4 @@ int clip_is_minicpmv(const struct clip_ctx * ctx) {
 
 bool clip_is_glm(const struct clip_ctx * ctx) {
     return ctx->has_glm_projector;
-}
\ No newline at end of file
+}
diff --git a/examples/llava/glmedge-convert-image-encoder-to-gguf.py b/examples/llava/glmedge-convert-image-encoder-to-gguf.py
index ac1911a14..848ef1cf3 100644
--- a/examples/llava/glmedge-convert-image-encoder-to-gguf.py
+++ b/examples/llava/glmedge-convert-image-encoder-to-gguf.py
@@ -22,7 +22,7 @@ def should_skip_tensor(name: str, has_text: bool, has_vision: bool, has_llava: b
         "vision_model.embeddings.position_ids",
     ):
         return True
-    
+
     if name in (
         "vision_model.head.probe",
         "vision_model.head.attention.in_proj_weight",
@@ -220,7 +220,7 @@ fout.add_bool("clip.use_gelu", True)
 
 
 if has_glm_projector:
-    # model.vision_model.encoder.layers.pop(-1)  # pyright: ignore[reportAttributeAccessIssue] 
+    # model.vision_model.encoder.layers.pop(-1)  # pyright: ignore[reportAttributeAccessIssue]
     projector = torch.load(args.llava_projector)
     for name, data in projector.items():
         name = get_tensor_name(name)
@@ -277,4 +277,4 @@ fout.write_kv_data_to_file()
 fout.write_tensors_to_file()
 fout.close()
 
-print("Done. Output file: " + fname_out)
\ No newline at end of file
+print("Done. Output file: " + fname_out)