import gradio as gr | |
from transformers import pipeline | |
pipe = pipeline("question-answering", model="AlexKay/xlm-roberta-large-qa-multilingual-finedtuned-ru") | |
def main(question, context): | |
answer = pipe(question=question, context=context) | |
return answer["answer"] | |
with gr.Blocks() as demo: | |
gr.Markdown("""# Question Answerer!""") | |
with gr.Row(): | |
with gr.Column(): | |
text1 = gr.Textbox( | |
label="Question", | |
lines=1, | |
value="Who does Cristiano Ronaldo play for?", | |
) | |
text2 = gr.Textbox( | |
label="Context", | |
lines=3, | |
value="Cristiano Ronaldo is a player for Manchester United", | |
) | |
output = gr.Textbox() | |
b1 = gr.Button("Ask Question!") | |
b1.click(main, inputs=[text1, text2], outputs=output) | |
gr.Markdown("""#### powered by [Tassle](https://bit.ly/3LXMklV)""") | |
if __name__ == "__main__": | |
demo.launch() |