Model reference · open weights

paraphrase-multilingual-MiniLM-L12-onnx-Q

Embeddings Qdrant Embeddings 1 build Open weights 399k dl/mo

paraphrase-multilingual-MiniLM-L12-onnx-Q is an open-weight embedding model from Qdrant.

  • paraphrase-multilingual-MiniLM-L12-onnx-Q is a quantized ONNX port of the sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 model, developed by Qdrant.
  • It is designed for text classification and similarity searches, with a context length of 512 tokens.
  • The model is released under the apache-2.0 licence.

Summary of the Qdrant/paraphrase-multilingual-MiniLM-L12-v2-onnx-Q model card, 2026-10-01

What it is

Released byQdrant
Released2024-01-16

From the model card

What Qdrant says about paraphrase-multilingual-MiniLM-L12-onnx-Q

Read the model card

Quantized ONNX port of sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 for text classification and similarity searches.

Usage

Here's an example of performing inference using the model with FastEmbed.

from fastembed import TextEmbedding

documents = [
    "You should stay, study and sprint.",
    "History can only prepare us to be surprised yet again.",
]

model = TextEmbedding(model_name="sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2")
embeddings = list(model.embed(documents))

# [
#     array([1.96449570e-02, 1.60677675e-02, 4.10149433e-02...]),
#     array([-1.56669170e-02, -1.66313536e-02, -6.84525725e-03...])
# ]

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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