added embeds projection

app.py

@@ -1,5 +1,5 @@
-import torch
 import streamlit as st
+from sklearn.decomposition import PCA
 from sentence_transformers import SentenceTransformer
 
 st.set_page_config(layout='wide')
@@ -14,6 +14,11 @@ def get_model() -> SentenceTransformer:
     return SentenceTransformer('panalexeu/xlm-roberta-ua-distilled')
 
 
+@st.cache_resource
+def get_pca() -> PCA:
+    return PCA(n_components=2)
+
+
 st.title('xlm-roberta-ua-distilled')
 
 # define state
@@ -57,5 +62,4 @@ with right_column:
 
     if compute_btn := st.button('Compute', icon='🤖'):
         embeds = get_model().encode(st.session_state['sentences'])
-        for embed in embeds:
-            st.write(embed)
+        proj_points = get_pca().fit_transform(embeds)