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import streamlit as st | |
from langchain.llms import HuggingFaceHub | |
def get_answer(question,model_name="google/flan-t5-large"): | |
model=HuggingFaceHub(repo_id=model_name) | |
return model(question) | |
st.set_page_config( | |
page_title="Simple Q&A App", | |
page_icon=":robot:" | |
) | |
st.header("Do It!!!! Ask the Question.....") | |
col1,col2=st.columns([5,3]) | |
question=col1.text_area("Question:") | |
model_name=col2.selectbox("Model Name",options=["google/flan-t5-large","deepset/roberta-base-squad2","AmazonScience/qanlu","gpt2-medium","EleutherAI/gpt-neo-125m"]) | |
submit=st.button("Submit") | |
if submit: | |
with st.spinner("In progress..."): | |
response=get_answer(question,model_name) | |
st.subheader("Response") | |
st.write(f"{response}") |