Update README.md

README.md

@@ -46,7 +46,7 @@ This model was trained using knowledge distillation from the [IBM Granite-278M](
 
 ### Using Transformers
 
-```
+```Python
 from transformers import AutoModel, AutoTokenizer
 import torch
 import torch.nn.functional as F
@@ -72,7 +72,7 @@ print(f"Similarity: {similarity.item():.4f}")
 
 ### Using Sentence-Transformers
 
-```
+```Python
 from sentence_transformers import SentenceTransformer
 from sentence_transformers.util import cos_sim
 
@@ -86,23 +86,6 @@ similarity = cos_sim(embeddings, embeddings)
 print(f"Similarity: {similarity.item():.4f}")
 ```
 
-======================================================================
-COMPARING INFERENCE SPEED (Student vs Teacher)
-======================================================================
-Average inference time over 100 runs with 10 sentences (max_length=128):
-  Teacher Model: 17.944 ms
-  Student Model: 2.759 ms
-  Student is 6.5x faster than Teacher.
-
-  CPU speed comparision
-
-======================================================================
-COMPARING INFERENCE SPEED (Student vs Teacher)
-======================================================================
-Average inference time over 100 runs with 10 sentences (max_length=128):
-  Teacher Model: 269.578 ms
-  Student Model: 11.577 ms
-  Student is 23.3x faster than Teacher.
 
 ## Performance