How to use clips/e5-small-v2-t2t with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("clips/e5-small-v2-t2t") 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 clips/e5-small-v2-t2t with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("clips/e5-small-v2-t2t") model = AutoModelForCausalLM.from_pretrained("clips/e5-small-v2-t2t", device_map="auto")
