Upload app.py

app.py

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+import streamlit as st
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
+
+# Load LLAMA model and tokenizer
+model_name = "sujra/insurance_Model"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+# Define function for generating text
+#
+def generate_text(prompt):
+    pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200)
+    result = pipe(f"<s>[INST] {prompt} [/INST]")
+    generated_text = result[0]['generated_text']
+    return generated_text
+
+st.title("Insurance Response Generation")
+
+prompt_input = st.text_input("Enter your prompt:")
+
+if st.button("Generate Response"):
+    if prompt_input:
+        with st.spinner("Generating response..."):  # Display a spinner while generating response
+            response = generate_text(prompt_input)
+        st.write("Generated Response:")
+        st.write(response)
+    else:
+        st.write("Please enter a prompt.")