How to use n2vec/sentence-transformers_msmarco-MiniLM-L6-cos-v5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("n2vec/sentence-transformers_msmarco-MiniLM-L6-cos-v5") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
How to use n2vec/sentence-transformers_msmarco-MiniLM-L6-cos-v5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("n2vec/sentence-transformers_msmarco-MiniLM-L6-cos-v5") model = AutoModel.from_pretrained("n2vec/sentence-transformers_msmarco-MiniLM-L6-cos-v5")
What is a pickle import?
