This is the ONNX version of the Sentence Transformers model sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 for sentence embedding, optimized for speed and lightweight performance. By utilizing onnxruntime and tokenizers instead of heavier libraries like sentence-transformers and transformers, this version ensures a smaller library size and faster execution. Below are the details of the model:
This ONNX model consists all components in the original sentence transformer model:
Transformer, Pooling
Using this model becomes easy when you have
LightEmbed installed:
1from light_embed import TextEmbedding
2sentences = ["This is an example sentence", "Each sentence is converted"]
3
4model = TextEmbedding('sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2')
5embeddings = model.encode(sentences)
6print(embeddings)
