pentest-orca-pi07

Standard 6-layer BERT sentence embedding model.

Model Description

A compact BERT model producing 256-dimensional sentence embeddings.

• Architecture: BertModel (6 layers, 256 hidden, 4 heads)
• Output: 256-dimensional embeddings
• Use cases: Semantic search, RAG retrieval

Serving Configuration

• Container: huggingface-pytorch-inference:2.4.0-transformers4.46.0-cpu-py311-ubuntu22.04
• Instance: ml.m5.xlarge
• Workers: 2

Usage

from sentence_transformers import SentenceTransformer
m = SentenceTransformer("jasonecktest01/pentest-orca-pi07")
e = m.encode(["Hello world"])

Citation

@article{pentest-orca-pi07-2026,
  title={Lightweight BERT Embeddings},
  author={Research Team},
  year={2026}
}

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