Create app.py

app.py

@@ -0,0 +1,21 @@
+import gradio as gr
+import torch
+from huggingface_hub import hf_hub_download
+
+model_path = hf_hub_download(repo_id="Mbilal755/Radiology_Bart", filename="pytorch_model.bin")
+model = torch.load(model_path)
+
+# Load tokenizer
+tokenizer = hf_hub_download(repo_id="Mbilal755/Radiology_Bart", filename="tokenizer.json") 
+tokenizer = tokenizer.tokenizer
+
+def summarize(text):
+  inputs = tokenizer(text, return_tensors="pt") 
+  summary_ids = model.generate(inputs["input_ids"])  
+  summary = tokenizer.decode(summary_ids[0])
+  return summary
+
+iface = gr.Interface(fn=summarize, inputs="text", outputs="text")
+
+if __name__ == "__main__":
+  iface.launch(share=True)