Update README.md

README.md

@@ -33,23 +33,30 @@ Context Length	2048 tokens
     #
     from transformers import AutoTokenizer, AutoModelForCausalLM
     import torch
-
+    
     # Load tokenizer & model
     tokenizer = AutoTokenizer.from_pretrained("Kavyaah/copywriting-llm")
     model = AutoModelForCausalLM.from_pretrained("Kavyaah/copywriting-llm", torch_dtype="auto")
     model.eval()
-
+    
     # Function to generate push notification
     def generate_copy(brand, offer, tone="fun", max_new_tokens=40):
         prompt = f"""You are an expert marketing copywriter.
     Write a short, catchy push notification in a {tone} tone.
     It should promote {brand}'s offer: "{offer}".
     Keep it under 20 words, engaging, and persuasive."""
-      inputs = tokenizer(prompt, return_tensors="pt")
-      with torch.no_grad():
-          outputs = model.generate(**inputs, max_new_tokens=max_new_tokens, temperature=0.9, top_p=0.9, do_sample=True)
-      return tokenizer.decode(outputs[0], skip_special_tokens=True)
-
+        
+        inputs = tokenizer(prompt, return_tensors="pt")
+        with torch.no_grad():
+            outputs = model.generate(
+                **inputs,
+                max_new_tokens=max_new_tokens,
+                temperature=0.9,
+                top_p=0.9,
+                do_sample=True
+            )
+        return tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
 # Example
     print(generate_copy("Zomato", "Flat 60% off on dinner combos this weekend!"))
     #