sentence-transformers How to use s2593817/sft-sql-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("s2593817/sft-sql-embedding")
sentences = [
"SELECT DISTINCT count(alias3.col1) , alias1.col2 FROM table1 AS alias1 JOIN table2 AS alias2 ON alias1.col2 = alias2.col2 JOIN table3 AS alias3 ON alias1.col1 = alias3.col1 WHERE alias2.col3 = str AND alias3.year = num GROUP BY alias1.col2",
"SELECT col1 , avg(col2) FROM table1 WHERE col3 LIKE str GROUP BY col1",
"SELECT col1 , col2 FROM table1 WHERE col3 LIKE str GROUP BY col1 ORDER BY count(*) DESC LIMIT num",
"SELECT col1 , avg(col2) FROM table1 GROUP BY col1 ORDER BY avg(col2)"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
