Sentence Similarity
sentence-transformers
ONNX
Safetensors
modernbert
semantic-router
vela
matryoshka
text-embeddings-inference
Instructions to use vllm-sr/Vela-1.0-Encoder-307M-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use vllm-sr/Vela-1.0-Encoder-307M-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vllm-sr/Vela-1.0-Encoder-307M-Embedding") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
13 days ago
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Update Hugging Face org references: llm-semantic-router → vllm-sr
Verified signature290318f
29 days ago
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Expand encoder retrieval coverage with matching exports and measured scores
Verified signatureUpdate the encoder and matching exports, refresh only product-page scores, preserve the opt-in AMD helper, and retain complete measured trade-offs in the separate evaluation evidence.972c180 -
Update encoder with additional Chinese retrieval training and matching exports
Verified signatureUpdate the encoder and matching exports, refresh only product-page scores, preserve the opt-in AMD helper, and retain complete measured trade-offs in the separate evaluation evidence.bc1093b
30 days ago
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Update retrieval-distilled encoder and matching exports
Verified signatureUpdate the encoder and matching exports, refresh only product-page scores, and retain detailed evaluation evidence separately. Small classification, retrieval and long-document point gains, alongside clustering and representation-grid regressions, remain visible in the measured results.75c25cd -
Refine retrieval and multi-resolution embeddings
Verified signatureUpdate the encoder and matching exports, refresh only product-page scores, and retain detailed evaluation evidence separately. Long-document, clustering and cross-language trade-offs remain visible in the measured results.9952e61 -
Improve multilingual classification and long-document retrieval
Verified signatureUpdate the encoder and matching exports, refresh only product-page scores, and retain detailed evaluation evidence separately. Short-retrieval regressions remain visible in the measured results.27cf105 -
Publish R3 interim encoder: classification and long retrieval gains with disclosed tradeoffs
Verified signatureAtomic native weights, tokenizer/config, eight standard/CK ONNX graphs and shared weights, model card, and complete bounded evaluation evidence. Native FP32 scores compare primarily with mmBERT. Short retrieval and early-exit regressions remain visible; this is not a full-MMTEB or universal-superiority claim.ae3a92a