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import streamlit as st | |
import single | |
import corpus | |
from PIL import Image | |
PAGES = { | |
"Instance Explanation": single, | |
"Dataset Explanation": corpus, | |
} | |
logo = Image.open("static/logo.png") | |
st.sidebar.image(logo) | |
st.sidebar.title("*ferret* showcase") | |
st.sidebar.markdown( | |
""" | |
Welcome to the *ferret* showcase! | |
You will find two main functionalities. | |
""" | |
) | |
page = st.sidebar.radio("", list(PAGES.keys())) | |
st.sidebar.markdown( | |
""" | |
In the single-*instance* page, you can evaluate our built-in explainers on your favourite model. | |
Choosing *dataset* mode, you will evaluate explainers on state-of-the-art datasets from our Dataset API. | |
""" | |
) | |
PAGES[page].body() | |