Update app.py

code added for Med QnA

app.py

@@ -1,10 +1,35 @@
-import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoModelWithLMHead
+import gradio
 
-def greet(name):
-    return "Hello " + name + "!!"
+username = "SrdharMahendran"      # change it to your HuggingFace username
+model_path = username + '/MedQnA_Model'
+tokenizer_path = username + '/MedQnA_Tokenizer'
 
-iface = gr.Interface(fn=greet, 
+loaded_model = AutoModelWithLMHead.from_pretrained(model_path)
+loaded_tokenizer = AutoTokenizer.from_pretrained(tokenizer_path)
+
+def generate_query_response(prompt, max_length=200):
+
+    model = loaded_model
+    tokenizer = loaded_tokenizer
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")      # 'pt' for returning pytorch tensor
+
+    # Create the attention mask and pad token id
+    attention_mask = torch.ones_like(input_ids)
+    pad_token_id = tokenizer.eos_token_id
+
+    output = model.generate(
+        input_ids,
+        max_length=max_length,
+        num_return_sequences=1,
+        attention_mask=attention_mask,
+        pad_token_id=pad_token_id
+    )
+
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+iface = gradio.Interface(fn=generate_query_response, 
                      inputs="text", 
                      outputs="text",
                      title = "MedQnA Application")
-iface.launch()
+iface.launch()