Create app.py

app.py

@@ -0,0 +1,56 @@
+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+
+def load_model():
+    # Load the English to Urdu translation model
+    model_name = "Helsinki-NLP/opus-mt-en-ur"
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    model = MarianMTModel.from_pretrained(model_name)
+    return tokenizer, model
+
+def translate_text(text, tokenizer, model):
+    """
+    Translate English text to Urdu using the loaded model
+    """
+    # Tokenize the input text
+    inputs = tokenizer(text, return_tensors="pt", padding=True)
+    
+    # Generate translation
+    translated = model.generate(**inputs)
+    
+    # Decode the translation
+    translated_text = tokenizer.batch_decode(translated, skip_special_tokens=True)[0]
+    
+    return translated_text
+
+def main():
+    # Load the model and tokenizer
+    tokenizer, model = load_model()
+    
+    # Define the Gradio interface
+    iface = gr.Interface(
+        fn=lambda text: translate_text(text, tokenizer, model),
+        inputs=gr.Textbox(
+            lines=5, 
+            placeholder="Enter English text here...",
+            label="English Text"
+        ),
+        outputs=gr.Textbox(
+            lines=5,
+            label="Urdu Translation"
+        ),
+        title="English to Urdu Translator",
+        description="Enter English text and get its Urdu translation",
+        examples=[
+            ["Hello, how are you?"],
+            ["I love learning new languages."],
+            ["The weather is beautiful today."]
+        ],
+        theme=gr.themes.Soft()
+    )
+    
+    # Launch the interface
+    iface.launch()
+
+if __name__ == "__main__":
+    main()