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import plotly.express as px
import streamlit as st
from sentence_transformers import SentenceTransformer
import umap.umap_ as umap
import pandas as pd
import os
import joblib
def app():
with st.container():
question = st.text_input("Please enter your text here and we will embed it for you.",
value="Woman",)
if st.button("Embed"):
with st.spinner("👑 load language model (sentence transformer)"):
model_name = 'sentence-transformers/all-MiniLM-L6-v2'
model = SentenceTransformer(model_name)
umap_name = "peter2000/umap_embed_3d_all-MiniLM-L6-v2"
umap_model = joblib.load(umap_name)
docs_umap = umap_model.transform(docs_embeddings)
examples_embeddings = model.encode(question)
examples_umap = umap_model.transform(examples_embeddings)
st.write(examples_umap.shape) |