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import gradio as gr | |
from transformers import pipeline | |
# Load the VQA model | |
oracle = pipeline(model="dandelin/vilt-b32-finetuned-vqa") | |
# Define a function to use the model | |
def answer_question(image, question): | |
response = oracle(question=question, image=image) | |
return response[0]['answer'] | |
# Import the specific input and output components directly | |
from gradio import Image, Textbox | |
# Create the Gradio interface | |
interface = gr.Interface( | |
fn=answer_question, | |
inputs=[Image(type="filepath"), Textbox()], | |
outputs=Textbox() | |
) | |
# Launch the app | |
interface.launch() |