Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+# Load the English-to-Urdu translation model from Hugging Face
+model_name = "Helsinki-NLP/opus-mt-en-ur"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+def translate_english_to_urdu(text):
+    """Translate input English text to Urdu."""
+    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512)
+    output_tokens = model.generate(**inputs)
+    translated_text = tokenizer.decode(output_tokens[0], skip_special_tokens=True)
+    return translated_text
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("<h1 align='center'>🌍 English to Urdu Translator</h1>")
+    
+    with gr.Row():
+        input_text = gr.Textbox(label="Enter English Text", placeholder="Type here...")
+        output_text = gr.Textbox(label="Translated Urdu Text", interactive=False)
+
+    translate_button = gr.Button("Translate")
+
+    translate_button.click(translate_english_to_urdu, inputs=input_text, outputs=output_text)
+
+# Launch the app
+demo.launch()