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# Import the required libraries | |
import streamlit as st | |
from transformers import pipeline | |
# Create a calculator function using the Llama model | |
def calculator(expression): | |
# Initialize the Llama model from Hugging Face | |
model = pipeline("text2text-generation", model="EleutherAI/llama") | |
# Generate the answer using the model | |
answer = model(expression)[0]["generated_text"] | |
# Return the answer | |
return answer | |
# Create a Streamlit app to display the calculator | |
st.title("Calculator using Llama model") | |
# Get the user input | |
expression = st.text_input("Enter an expression to calculate:") | |
# Check if the input is not empty | |
if expression: | |
# Call the calculator function and display the answer | |
answer = calculator(expression) | |
st.write(f"The answer is: {answer}") | |