How to use NghiemAbe/Vi-Legal-Bi-Encoder-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NghiemAbe/Vi-Legal-Bi-Encoder-v2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3]
How to use NghiemAbe/Vi-Legal-Bi-Encoder-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("NghiemAbe/Vi-Legal-Bi-Encoder-v2") model = AutoModel.from_pretrained("NghiemAbe/Vi-Legal-Bi-Encoder-v2")
