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from sentence_transformers import SentenceTransformer, SimilarityFunction
import streamlit as st
model_name = "nomic-ai/nomic-embed-text-v2-moe"
with st.form("embedding"):
sentence1 = st.text_inupt("Sentence 1:","Hello!")
sentence2 = st.text_inupt("Sentence 2:","¡Hola!")
sim_fun = st.selectbox('Similarity Function', ['COSINE', 'DOT_PRODUCT', 'EUCLIDEAN', 'MANHATTAN'])
calculate = st.form_submit_button('Calculate')
if calculate:
model = SentenceTransformer(model_name, trust_remote_code=True)
sentences = [sentence1, sentence2]
embeddings = model.encode(sentences, prompt_name="passage")
similarity_fn_enum = getattr(SimilarityFunction, sim_fun)
model.similarity_fn_name = similarity_fn_enum
similarities = model.similarity(embeddings[0], embeddings[1])
st.write(f"similarity: {similarities}")
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