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Create app.py
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app.py
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import gradio as gr
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import torch
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from huggingface_hub import hf_hub_download
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model_path = hf_hub_download(repo_id="Mbilal755/Radiology_Bart", filename="pytorch_model.bin")
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model = torch.load(model_path)
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# Load tokenizer
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tokenizer = hf_hub_download(repo_id="Mbilal755/Radiology_Bart", filename="tokenizer.json")
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tokenizer = tokenizer.tokenizer
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def summarize(text):
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inputs = tokenizer(text, return_tensors="pt")
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summary_ids = model.generate(inputs["input_ids"])
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summary = tokenizer.decode(summary_ids[0])
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return summary
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iface = gr.Interface(fn=summarize, inputs="text", outputs="text")
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if __name__ == "__main__":
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iface.launch(share=True)
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