import streamlit as st | |
def demo(): | |
#st.write("yes its work") | |
pass | |
def run_example(image, model, processor, task_prompt, text_input=None): | |
inputs = processor(text=text_input, images=image, return_tensors="pt") | |
generated_ids = model.generate( | |
input_ids=inputs["input_ids"], | |
pixel_values=inputs["pixel_values"], | |
max_new_tokens=1024, | |
num_beams=4 | |
) | |
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] | |
print("generated_text:",generated_text) | |
# parsed_answer = processor.post_process_generation(generated_text, task=task_prompt, image_size=(image.width, image.height)) | |
return generated_text | |