sentence-transformers How to use NickyNicky/StaticEmbedding-MatryoshkaLoss-gemma-2-2b-en-es with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("NickyNicky/StaticEmbedding-MatryoshkaLoss-gemma-2-2b-en-es")
sentences = [
"how to sign legal documents as power of attorney?",
"After the principal's name, write “by” and then sign your own name. Under or after the signature line, indicate your status as POA by including any of the following identifiers: as POA, as Agent, as Attorney in Fact or as Power of Attorney.",
"['From the Home screen, swipe left to Apps.', 'Tap Transfer my Data.', 'Tap Menu (...).', 'Tap Export to SD card.']",
"Ginger Dank Nugs (Grape) - 350mg. Feast your eyes on these unique and striking gourmet chocolates; Coco Nugs created by Ginger Dank. Crafted to resemble perfect nugs of cannabis, each of the 10 buds contains 35mg of THC. ... This is a perfect product for both cannabis and chocolate lovers, who appreciate a little twist."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
