Update app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load your model and tokenizer
+model_name = "Amir230703/phi3-medmcqa-finetuned"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
+
+# Define function for inference
+def generate_response(prompt):
+    input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+    with torch.no_grad():
+        output = model.generate(input_ids, max_length=200)
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+# Create Gradio UI
+iface = gr.Interface(
+    fn=generate_response,
+    inputs="text",
+    outputs="text",
+    title="Medical QA Model",
+    description="Enter a medical question, and the AI will provide an answer."
+)
+
+iface.launch()