How to use nlplabtdtu/gte-small-senformer with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nlplabtdtu/gte-small-senformer") 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 nlplabtdtu/gte-small-senformer with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nlplabtdtu/gte-small-senformer") model = AutoModel.from_pretrained("nlplabtdtu/gte-small-senformer", device_map="auto")
