---
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

```python
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 |