from sentence_transformers import SentenceTransformer, SimilarityFunction

import streamlit as st

st.
x = st.slider('Select a value')
st.write(x, 'squared is', x * x)

model = SentenceTransformer(model_name, trust_remote_code=True)
embeddings = model.encode(sentences, prompt_name="passage")

similarity_fn_enum = getattr(SimilarityFunction, similarity_fn.upper())
model.similarity_fn_name = similarity_fn_enum

similarities = model.similarity(embeddings[0], embeddings[1])
print(f"similarity: {similarities}")