How to use LightEmbed/sbert-all-MiniLM-L12-v2-onnx with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LightEmbed/sbert-all-MiniLM-L12-v2-onnx") 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/LightEmbed/sbert-all-MiniLM-L12-v2-onnx/resolve/main/tokenizer.json
hf download hf://LightEmbed/sbert-all-MiniLM-L12-v2-onnx/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/LightEmbed/sbert-all-MiniLM-L12-v2-onnx/resolve/main/tokenizer.json
