import gradio as gr from transformers import pipeline #from fairseq.models.transformer import TransformerModel # Load the English to Urdu translation model from the transformers library model_name_or_path = "samiulhaq/iwslt-bt-en-ur" #model_name_or_path = TransformerModel.from_pretrained('samiulhaq/iwslt-bt-en-ur') translator = pipeline("translation", model=model_name_or_path, tokenizer=model_name_or_path) # Create a Gradio interface for the translation app def translate(text): # Use the translator pipeline to translate the input text result = translator(text, max_length=500) return result[0]['translation_text'] input_text = gr.inputs.Textbox(label="Input English Text") output_text = gr.outputs.Textbox(label="Output Urdu Text") app = gr.Interface(fn=translate, inputs=input_text, outputs=output_text) # Launch the app app.launch()