nypgd/fine-tuned-sentence-transformer_last

pip install -U sentence-transformers
from sentence_transformers import SentenceTransformer
# Descargar desde el Hub de 🤗
model = SentenceTransformer("nypgd/fine-tuned-sentence-transformer_last")
# Ejecutar inferencia
sentences = [
"Eleanor Hunt'a ait kaç tane kiralama kimliği var?",
'CREATE TABLEcustomer (\n    customer_id INTEGER PRIMARY KEY,\n    store_id INTEGER,\n    first_name TEXT,\n    last_name TEXT,\n    email TEXT,\n    address_id INTEGER,\n    active INTEGER,\n    create_date DATETIME,\n    last_update DATETIME,\n    FOREIGN KEY (address_id) REFERENCES address(None),\n    FOREIGN KEY (store_id) REFERENCES store(None)\n);',
'CREATE TABLEdistrict (\n    District_ID INT PRIMARY KEY,\n    District_name TEXT,\n    Headquartered_City TEXT,\n    City_Population REAL,\n    City_Area REAL\n);',
]
embeddings = model.encode(sentences)
print(embeddings.shape) # [3, 768]
# Obtener los puntajes de similitud de las incrustaciones
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape) # [3, 3]