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mLateOn

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LightOn AI 765

Hello!

Starting with the next Sentence Transformers release (v6.0.0, planned for around the 18th), this checkpoint loads directly as a multi-vector (ColBERT-style late interaction) retriever through the new MultiVectorEncoder, alongside its existing PyLate usage. This PR adds a Sentence Transformers usage section to the model card and a multi-vector tag. The weights and the existing PyLate usage are untouched.

I'd love to feature this model in that release's blog post and documentation, especially once it loads without the revision pin (that is, once this PR is merged).

pip install "sentence-transformers @ git+https://github.com/huggingface/sentence-transformers.git"

from sentence_transformers import MultiVectorEncoder

model = MultiVectorEncoder("lightonai/mLateOn", revision="refs/pr/1")

query = "Which planet is the Red Planet?"
documents = [
    "Mars, known for its reddish appearance, is often referred to as the Red Planet.",
    "Mars, connu pour son apparence rougeâtre, est souvent appelé la planète rouge.",
    "Mars, bekannt für sein rötliches Erscheinungsbild, wird oft als der Rote Planet bezeichnet.",
    "Venus is often called Earth's twin because of its similar size and proximity.",
]

query_embeddings = model.encode_query(query)
document_embeddings = model.encode_document(documents)
print(query_embeddings.shape, document_embeddings[0].shape)
# (10, 128) (20, 128)

# MaxSim late-interaction scoring (higher is more relevant)
scores = model.similarity(query_embeddings, document_embeddings)
print(scores)
# tensor([[9.6029, 9.5838, 9.5877, 9.4578]])

• Tom Aarsen