light-embed/snowflake-arctic-embed-m-onnx

snowflake-arctic-embed-m-onnx

This is the ONNX version of the Sentence Transformers model Snowflake/snowflake-arctic-embed-m 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:

• —Base model: Snowflake/snowflake-arctic-embed-m
• —Embedding dimension: 768
• —Max sequence length: 512
• —File size on disk: 0.41 GB
• —Pooling incorporated: Yes

This ONNX model consists all components in the original sentence transformer model: Transformer, Pooling, Normalize

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Usage (LightEmbed)

Using this model becomes easy when you have LightEmbed installed:

pip install -U light-embed

Then you can use the model like this:

from light_embed import TextEmbedding
sentences = ["This is an example sentence", "Each sentence is converted"]

model = TextEmbedding('Snowflake/snowflake-arctic-embed-m')
embeddings = model.encode(sentences)
print(embeddings)

Citing & Authors

Binh Nguyen / binhcode25@gmail.com