Spaces:
Running
Running
File size: 1,060 Bytes
f11912b f68327f f11912b 4f7df78 f68327f 35c4462 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 |
import streamlit as st
from sklearn.metrics.pairwise import cosine_similarity
import numpy as np
from sentence_transformers import SentenceTransformer
def app():
st.title("Text Similarity")
model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
with st.container():
col1, col2 = st.columns(2)
with col1:
word_to_embed1 = st.text_input("Text 1", value="",)
with col2:
word_to_embed2 = st.text_input("Text 2", value="",)
if st.button("Embed"):
with st.spinner("Embedding comparing your inputs"):
document = [word_to_embed1 ,word_to_embed2]
#Encode paragraphs
document_embeddings = model.encode(document, show_progress_bar=False)
#Compute cosine similarity between labels sentences and paragraphs
similarity_matrix = cosine_similarity(label_embeddings, document_embeddings)
st.write("Text similarity:" similarity_matrix) |