qwen-0.6B-turkish-ecommerce-tuned-omnibusv2

pip install -U sentence-transformers

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("turanyigitpazarama/qwen-0.6B-turkish-ecommerce-tuned-omnibusv2")
# Run inference
queries = [
    "Instruct: Find complementary items frequently bought together with this product.\nQuery: Toyota auris oto branda ara\u00e7 \u00f6rt\u00fcs\u00fc 2007-",
]
documents = [
    'Toyota Auris (2006-2011) Araçlar için Led Xenon Kısa Far Aydınlatma Ampulu FEMEX Premio Plus H11',
    'Micro Fitted Full Kenar Su Sıvı Geçirmez Alez Çarşaf Tek Çift Kişilik Beyaz Renkli Yatak Koruyucu',
    'Kadın sarı altın ince zincirli, ortasında dikdörtgen formda baget kesim pırlanta ve zirkon taşlarla çevrili bir adet charm bulunan zarif kolye',
]
query_embeddings = model.encode_query(queries)
document_embeddings = model.encode_document(documents)
print(query_embeddings.shape, document_embeddings.shape)
# [1, 1024] [3, 1024]

# Get the similarity scores for the embeddings
similarities = model.similarity(query_embeddings, document_embeddings)
print(similarities)
# tensor([[0.5859, 0.2275, 0.0238]], dtype=torch.bfloat16)