Update app.py

app.py

@@ -1,5 +1,5 @@
 ## Deploying on HuggingFace
-## Deploying on HuggingFace
+
 import streamlit as st
 import pandas as pd
 import torch
@@ -41,7 +41,7 @@ def load_model():
 model, tokenizer = load_model()
 
 # Prediction function
-# Prediction function
+
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 def get_prediction(prompt):
@@ -67,7 +67,7 @@ def get_prediction(prompt):
     # Generate output using the model with streaming
     output = model.generate(
         inputs["input_ids"],  # Use the tokenized input
-        max_new_tokens=150,  # Limit the number of tokens
+        max_new_tokens=250,  # Limit the number of tokens
         temperature=0.7,  # Control randomness of output
         top_p=0.95,  # Sampling parameter
         do_sample=True,  # Ensure sampling for diverse output
@@ -139,3 +139,4 @@ with tab2:
                 csv_output = df.to_csv(index=False).encode("utf-8")
                 st.download_button("📤 Download Predictions", data=csv_output, file_name="predictions.csv")
 
+