How to use quancute/few_COT_bi_encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("quancute/few_COT_bi_encoder") 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 quancute/few_COT_bi_encoder with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("quancute/few_COT_bi_encoder") model = AutoModel.from_pretrained("quancute/few_COT_bi_encoder", device_map="auto")
https://huggingface.co/quancute/few_COT_bi_encoder/resolve/main/bpe.codes
hf download hf://quancute/few_COT_bi_encoder/bpe.codes
curl -L -o bpe.codes https://huggingface.co/quancute/few_COT_bi_encoder/resolve/main/bpe.codes
