Update app.py

app.py

@@ -1,4 +1,4 @@
-from transformers import AutoTokenizer, AutoModelForCausalLM
+"""from transformers import AutoTokenizer, AutoModelForCausalLM
 import gradio as gr
 import torch
 
@@ -31,3 +31,19 @@ iface = gr.Interface(
 )
 
 iface.launch()
+"""
+from transformers import pipeline
+import gradio as gr
+
+# Load a pre-trained model (using mBART here for multilingual text generation)
+model = pipeline("text2text-generation", model="facebook/mbart-large-50-many-to-one-mmt")
+
+def convert_to_casual_hindi(text):
+    # Use the model to transform the text dynamically
+    # We assume the model will handle Hindi text and convert it
+    transformed_text = model(text)
+    return transformed_text[0]['generated_text']
+
+# Gradio interface for deployment in Hugging Face Spaces
+iface = gr.Interface(fn=convert_to_casual_hindi, inputs="text", outputs="text", title="Formal to Casual Hindi Converter")
+iface.launch()