sentence-transformers How to use llmvetter/embedding_finetune with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("llmvetter/embedding_finetune")
sentences = [
"samsung ms23h3125ak/ms23h3125ak",
"Canon EOS M50 + 15-45mm IS STM",
"Bosch KIV32X23GB Integrated",
"Indesit DIF04B1 Integrated",
"Samsung MS23H3125AK Black",
"Samsung RB29FWRNDBC Black",
"Hisense RQ560N4WC1",
"Samsung UE32M5520",
"Nikon CoolPix A10",
"Hotpoint RPD10457JKK",
"HP Intel Xeon X5670 2.93GHz Socket 1366 3200MHz bus Upgrade Tray",
"Indesit DFG15B1S Silver",
"Samsung WW10M86DQOO",
"Bosch SMV46MX00G Integrated",
"LG 49SK8100PLA",
"Nikon CoolPix W300",
"AMD Ryzen 3 1300X 3.5GHz Box",
"LG OLED65B8PLA",
"Samsung Galaxy J5 SM-J530",
"LG 65UK6500PLA",
"Siemens WM14T391GB",
"Apple iPhone SE 32GB"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [22, 22] 
