Update app.py

app.py

@@ -1,21 +1,19 @@
-import keras_nlp
-from keras_nlp.models import GemmaCausalLM
-import warnings
-warnings.filterwarnings('ignore')
-import os
+from transformers import pipeline
 
-
-
-model = keras_nlp.models.CausalLM.from_preset(f"hf://soufyane/gemma_data_science")
+# Load the model
+model_name = "soufyane/gemma_data_science"
+text_generator = pipeline("text-generation", model=model_name)
 
 def process_text_gemma(input_text):
-    response = model.generate(f"question: {input_text}", max_length=256)
+    # Generate text using the model
+    response = text_generator(f"question: {input_text}", max_length=256)[0]['generated_text']
     return response
 
-
 def main(input_text):
     return process_text_gemma(input_text[0])
 
+import gradio as gr
+
 gr.Interface(
     fn=main,
     inputs=["text"],