sentence-transformers How to use swardiantara/bert-tiny-amazon_reviews-k3-fixed-euclidean with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("swardiantara/bert-tiny-amazon_reviews-k3-fixed-euclidean")
sentences = [
"I received my first order of this product and it was broke so I ordered it again. The second one was broke in more places than the first. I can't blame the shipping process as it's shrink wrapped and boxed.",
"My second one; so far they've held up just find. This one has been in daily use for work, all the zippers continue to work just fine. A metal jug of hot coffee is often in the main pocket, but I've never felt any heat from it. So far, these and the SOG Ninja packs are a very good deal for what they cost.",
"I have had mine for 3 months now and all the bling is still in tact! Which is a huge plus for me. I always notice that’s always the first thing to mess up. Cute keychain! Love it.",
"I ordered two of these. One came broken. It was packaged okay, so I believe it was broken due to the mail carrier tossing it onto my porch. The one that did not break, I love. It looks nice on my counter and serves its purpose. Updated review: Ok so the salt cellar that did not break during shipping pretty much shattered at the lightest touch after 3 weeks on my counter. I can no longer recommend this item, clearly they are not very durable at all."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
