Instructions to use HideIron/tiny-aya-global-sql-selfheal-bco-replay with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use HideIron/tiny-aya-global-sql-selfheal-bco-replay with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("CohereLabs/tiny-aya-global") model = PeftModel.from_pretrained(base_model, "HideIron/tiny-aya-global-sql-selfheal-bco-replay") - Notebooks
- Google Colab
- Kaggle
tiny-aya-global-sql-selfheal-bco-replay (BCO + success replay). Deployed.
LoRA adapter for CohereLabs/tiny-aya-global (3.35B) from a fully automated self-healing text-to-SQL loop (Lexsi Labs Hackathon, Track 3, PS #8). Failures are detected by executing the SQL on real Spider databases, classified, corrected by Aya Expanse 32B (every fix verified by execution; the healer never sees the gold query), and retrained through AgentTune. Deployment is decided by AgentTune's DeploymentGate on held-out data.
Recipe: BCO with success replay: 153 verified fixes (True) + 153 wrong queries (False) + the model's own 347 correct pool answers as independent positive rows (impossible under DPO's pairing requirement). 653 rows, 82 steps.
Result: APPROVED by the DeploymentGate on a 400-question held-out gate (59.25% vs 59.0%, recommendation deploy). On the unseen 500-question test split: 47.6% execution accuracy vs 45.6% baseline (+2.0pp, fixed 34 / broke 24), valid-SQL rate 73.0% vs 68.2%. Independently re-verified by AuditKIT (500/500 agreement).
- Project page + code: https://huggingface.co/spaces/HideIron/selfheal-sql
- All run logs and gate decisions: https://huggingface.co/datasets/HideIron/selfheal-sql-runs
- Training data: 158 execution-verified fix pairs (heal/baseline-pool600 in the runs repo)
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