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pplx-embed-v1-late-0.6b

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Perplexity 2.78k

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 the multi-vector and sentence-transformers tags. The weights and the existing 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("perplexity-ai/pplx-embed-v1-late-0.6b", trust_remote_code=True)

query = "What motivates scientific discovery?"
documents = [
    "Scientists explore the universe driven by curiosity.",
    "Children learn through curious exploration.",
    "Historical discoveries began with curious questions.",
]

query_embeddings = model.encode_query(query)
document_embeddings = model.encode_document(documents)
print(query_embeddings.shape, document_embeddings[0].shape)
# (32, 128) (8, 128)

# MaxSim late-interaction scoring (higher is more relevant)
scores = model.similarity(query_embeddings, document_embeddings)
print(scores)
# tensor([[31.4841, 31.2462, 31.4041]])

• Tom Aarsen