How to use McGill-NLP/bge-small-dmr with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("McGill-NLP/bge-small-dmr") 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 McGill-NLP/bge-small-dmr with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("McGill-NLP/bge-small-dmr", device_map="auto")
