app.py

# import gradio as gr

# from transformers import pipeline




# def translate(text,number):
#     model1=''
#     if number==1:
#         model1='Helsinki-NLP/opus-mt-en-es'
#     elif number==2:
#         model1='Helsinki-NLP/opus-mt-en-fr'
#     else:
#         model1='Helsinki-NLP/opus-mt-en-ru'

#     pipe=pipeline("translation", model=model1)  
#     return  pipe(text)[0]["translation_text"]




# demo = gr.Interface(fn=translate, inputs=["text","number"], outputs="json")
# demo.launch()




# import gradio as gr

# from transformers import pipeline

# pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ru")

# def predict(text):
#   return pipe(text)[0]["translation_text"]

# demo = gr.Interface(
#   fn=predict, 
#   inputs='text',
#   outputs='text',
# )

# demo.launch()



import gradio as gr

with gr.Blocks() as demo:
  with gr.Tab("Translate to Spanish"):
    gr.load("gradio/helsinki_translation_en_es", src="spaces")
  with gr.Tab("Translate to French"):
    gr.load("abidlabs/en2fr", src="spaces")

demo.launch()