Update app.py

app.py

@@ -9,6 +9,7 @@ g_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b")
 
 def Sentence_Commpletion(model_name, input_text):
     
+    
     if model_name == "Bloom":
         tokenizer, model = b_tokenizer, b_model
     elif model_name == "Gemma":
@@ -16,10 +17,10 @@ def Sentence_Commpletion(model_name, input_text):
     
     
     
-   inputs = tokenizer(input_text, return_tensors="pt")
-   outputs = model.generate(inputs.input_ids, max_length=50, num_return_sequences=1)
+    inputs = tokenizer(input_text, return_tensors="pt")
+    outputs = model.generate(inputs.input_ids, max_length=50, num_return_sequences=1)
     
-   return tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
 
 
 interface = gr.Interface(
@@ -27,10 +28,7 @@ fn=Sentence_Commpletion,
 inputs=[gr.Radio(["Bloom", "Gemma"], label="Choose model"),
         
         gr.Textbox(placeholder="Enter sentece"),],
-    outputs="text",
-    title="Bloom vs Gemma Sentence completion",
-    
-)
-
+outputs="text",
+title="Bloom vs Gemma Sentence completion",)
 
 interface.launch()