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"])