metadata
language: en
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- embeddings
- semantic-search
- contrastive-learning
library_name: sentence-transformers
pipeline_tag: feature-extraction
org-shared-embeddings
Shared embedding model for cross-team semantic search over documentation, runbooks, and resolved ticket summaries.
Hosted under the organization namespace for centralized inference endpoint billing.
Model description
| Property | Value |
|---|---|
| Base model | sentence-transformers/all-MiniLM-L6-v2 |
| Output dimension | 384 |
| Pooling | mean |
| Normalization | L2 |
| Max sequence length | 256 |
Intended use
- Internal doc search (
/v1/search/docs) - Duplicate ticket detection
- Clustering for QA review sampling
Usage
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("matt-ts/org-shared-embeddings")
query = "How do I rotate API keys for the staging environment?"
doc = "Staging key rotation: open IAM console, select service account..."
similarity = model.similarity(query, doc)
print(similarity) # tensor([[0.72]])
Deployment
| Endpoint | Region | Instance |
|---|---|---|
embeddings-prod-us |
us-east-1 | gpu-l4-small |
embeddings-prod-eu |
eu-west-1 | gpu-l4-small |
Version history
| Version | Date | Notes |
|---|---|---|
| v1.2.0 | 2026-01-08 | Added runbook corpus (+12k docs) |
| v1.1.0 | 2025-09-22 | Ticket summary fine-tune |
| v1.0.0 | 2025-06-01 | Initial MiniLM baseline |