Rad_Summarizer / app.py
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import gradio as gr
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model = AutoModelForSeq2SeqLM.from_pretrained("Mbilal755/Radiology_Bart")
tokenizer = AutoTokenizer.from_pretrained("Mbilal755/Radiology_Bart")
def summarize(input):
inputs = tokenizer(input, return_tensors="pt")
output = model.generate(inputs["input_ids"])
summary = tokenizer.decode(output[0], skip_special_tokens=True)
return summary
iface = gr.Interface(fn=summarize, inputs="text", outputs="text")
if __name__ == "__main__":
iface.launch(share=True)