How to use X13Core/ITS_embedding_bge_1000 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("X13Core/ITS_embedding_bge_1000") 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]
https://huggingface.co/X13Core/ITS_embedding_bge_1000/resolve/main/tokenizer.json
hf download hf://X13Core/ITS_embedding_bge_1000/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/X13Core/ITS_embedding_bge_1000/resolve/main/tokenizer.json
