pentest-orca-mw01

Standard 6-layer BERT sentence embedding model.

Model Description

A compact BERT model producing 256-dimensional sentence embeddings, fine-tuned on standard NLI corpora.

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

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-mw01")
e = m.encode(["Hello world"])