Create app.py

app.py

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+import streamlit as st
+from sentence_transformers.util import cos_sim
+from sentence_transformers import SentenceTransformer
+
+st.title("Sentence Embedding for Spanish with Bertin")
+st.write("Sentence embedding for spanish trained on NLI. Used for Sentence Textual Similarity.")
+
+sent1 = st.text_area('Enter sentence 1 ...')
+sent2 = st.text_area('Enter sentence 2 ...')
+
+model = SentenceTransformer('hackathon-pln-es/bertin-roberta-base-finetuning-esnli')
+
+if sent1 and sent2:
+  encodings = model.encode([sent1, sent2])
+  sim = cos_sim(encodings[0], encodings[1]).numpy().tolist()[0][0]
+  st.write('Cosine Similarity: {0:.4f}'.format(sim))