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router-v5-minilm
Ailiance-fr/router-v5-minilm
router-v5-minilm is a text classification model from Ailiance-fr. Use it when you need a label for a piece of text. It is set up for sentence-transformers. The card lists the license as apache-2.0.
Domain classifier head used by the ailiance gateway to route incoming chat requests to the most adapted backend worker.
Access
Public
Updated May 11, 2026
Repo size
427 KB
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Repo makeup
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.safetensors427 KB · 98%
At a glance
- Task
- Text Classification
- Library
- sentence-transformers
- License
- apache-2.0
- Access
- Public
- Created
- May 5, 2026
- Updated
- May 11, 2026
- SHA
- 6fb997a5
Try a prompt
Base models
Model card
From the Hugging Face model README
ailiance-router-v5 (MiniLM L6 v2 + 2-layer MLP)
Domain classifier head used by the ailiance gateway to route incoming chat requests to the most adapted backend worker.
Performance
- Top-1 accuracy: 87.6 %
- Top-3 accuracy: 98.7 %
- Validation set: 1 978 prompts across 32 domains.
Architecture
- Encoder:
sentence-transformers/all-MiniLM-L6-v2(frozen, 384d) - Head: 2-layer MLP
Linear(384→256) -> GELU -> Dropout(0.1) -> Linear(256→32) - Loss: BCE-with-logits (multi-label sigmoid)
- Optimizer: AdamW lr=1e-3, batch=128, 30 epochs, seed=42
🇪🇺 EU AI Act transparency
This artefact is published under the AI Act framework (Regulation EU 2024/1689).
| Field | Value |
|---|---|
| Provider | Ailiance (clemsail) |
| Role under AI Act | GPAI provider (this head). Encoder is upstream Microsoft / sentence-transformers under Apache-2.0. |
| Adapter type | Custom 2-layer MLP head (~85 k parameters) |
| Base model | sentence-transformers/all-MiniLM-L6-v2 |
| License | Apache-2.0 |
| Intended use | Domain routing only — classify a user prompt over 32 technical domains, decide which downstream worker handles the request. Not for standalone classification of safety-critical text. |
| Out of scope | Healthcare triage, legal classification, autonomous safety decisions, anything requiring calibrated probabilities. |
| Risk classification | Limited risk — Article 50 obligations apply. |
| Training data origin | All open permissive-licensed datasets + Ailiance in-house curation. Full per-source provenance: https://ailiance.fr/transparency/router-provenance |
| Reproducibility | https://ailiance.fr/transparency/router-rebuild-recipe |
| Contact | [email protected] |
Training data sources
| Domain group | Source dataset | License | Rows |
|---|---|---|---|
| python, rust, ts, cpp, shell, html-css, security, devops | sahil2801/CodeAlpaca-20k | CC-BY-4.0 | ~3 700 |
| sql | b-mc2/sql-create-context | CC-BY-4.0 | 805 |
| chat-fr | OpenAssistant/oasst1 (FR-filtered) | Apache-2.0 | 801 |
| math | openai/gsm8k | MIT | 803 |
| reasoning | AI-MO/NuminaMath-CoT | Apache-2.0 | 803 |
| spice, power, electronics | theprint/Electronics-QA | Apache-2.0 | ~1 500 |
| freecad | Yas1n/FreeCAD_Sketches (filename-derived) | CC-BY-4.0 | 602 |
| lua-upy | Roblox/luau_corpus | MIT | 603 |
| calcul-normatif, docker, FR/EN augment, greetings | Ailiance in-house | Apache-2.0 | 528 + 200 |
Total clean corpus: 9 817 prompts across 32 domains.
Files
router.safetensors— MLP head weightsmeta.json— encoder name, dim, head config, domain listlabel_map.json— domain ↔ index
Validated in ailiance/ailiance-bench v0.2
This model is referenced in the Ailiance benchmark suite (Phase 6 scoreboard, 7-task hardware-design evaluation).
See the full scoreboard: ailiance-bench README#scoreboard-lora-phase-6.
- Task
- Text Classification
- Library
- sentence-transformers
- License
- apache-2.0
- Languages
- en, fr
- Created
- May 5, 2026
- Updated
- May 11, 2026