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import gradio as gr
from transformers import BlipProcessor, BlipForConditionalGeneration
model_id = "dblasko/blip-dalle3-img2prompt"
model = BlipForConditionalGeneration.from_pretrained(model_id)
processor = BlipProcessor.from_pretrained(model_id)
def generate_caption(image):
inputs = processor(images=image, return_tensors="pt")
pixel_values = inputs.pixel_values
generated_ids = model.generate(pixel_values=pixel_values, max_length=50)
generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True, temperature=0.8, top_k=40, top_p=0.9)[0]
return generated_caption
# Create a Gradio interface with an image input and a textbox output
demo = gr.Interface(fn=generate_caption, inputs=gr.Image(), outputs=gr.Textbox(label="Generated caption"))
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