Update app.py

app.py

@@ -1,19 +1,20 @@
-from transformers import pipeline
+import keras_nlp
+from keras_nlp.models import GemmaCausalLM
+import warnings
+warnings.filterwarnings('ignore')
+import os
 
-# Load the model
-model_name = "soufyane/gemma_data_science"
-text_generator = pipeline("text-generation", model=model_name)
+
+model = keras_nlp.models.CausalLM.from_preset(f"hf://soufyane/gemma_data_science")
 
 def process_text_gemma(input_text):
-    # Generate text using the model
-    response = text_generator(f"question: {input_text}", max_length=256)[0]['generated_text']
+    response = model.generate(f"question: {input_text}", max_length=256)
     return response
 
+
 def main(input_text):
     return process_text_gemma(input_text[0])
 
-import gradio as gr
-
 gr.Interface(
     fn=main,
     inputs=["text"],
@@ -21,4 +22,4 @@ gr.Interface(
     title="Gemma Data Science Model",
     description="This is a text-to-text model for data science tasks.",
     live=True
-).launch()
+).launch()