import gradio as gr
from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering, AutoModelForCausalLM, AutoTokenizer
from PIL import Image
import torch

model = AutoModelForCausalLM.from_pretrained("microsoft/git-base-vqav2")
model_path = "microsoft/git-base-vqav2"
dataset_name = "Multimodal-Fatima/OK-VQA_train"
tokenizer = AutoTokenizer.from_pretrained(model_path)

def main():


demo = gr.Interface(
    fn=main,
    inputs=[gr.Slider(1, len(questions), step=1)],
    outputs=["image", "text", "text"],
)

demo.launch(share=True)