step2_load_model.py

from sentence_transformers import SentenceTransformer

MODEL_NAME = "keepitreal/vietnamese-sbert"

# Load model (lan dau se tu dong download)
model = SentenceTransformer(MODEL_NAME)
model.save("./models/keepitrealvietnamese-sbert")
print("Saved to ./models/keepitrealvietnamese-sbert")
# Test encode
test_text = "Kiem tra so chan le bang toan tu modulo va if else"
vec = model.encode(test_text, normalize_embeddings=True)

print("Model loaded:", MODEL_NAME)
print("Vector shape:", vec.shape)   # thuong la (384,)
print("Vector sample:", vec[:5])