---
language:
- en
- fr
license: other
base_model: LiquidAI/LFM2-24B-A2B
library_name: peft
pipeline_tag: text-generation
tags:
- wagmi
- deal-ex-machina
- sft
- lfm2
- auth
- merged
---

# Wagmi (lfm2/auth/sft) - merged

**Version:** 0.3.5  
**Repo ID:** `jeanbaptdzd/wagmi-lfm2-24b-auth-sft-merged`

## Model Summary

This model is part of the Wagmi assistant stack for Deal ex Machina. It is a `merged` artifact in the `lfm2` family (`auth` profile).

## Recent Training Updates

- **DPO safety path (14B / auth / qwen):** `train_dpo.py`, `data/dpo/wagmi_safety_dpo.jsonl`, Hub adapter `jeanbaptdzd/wagmi-qwen2.5-14b-sft-dpo`, merged `…-sft-dpo-merged`, GGUF `…-sft-dpo-gguf` (local export: `./scripts/local_gguf_export.sh auth-dpo`).
- **Space:** Gradio tabs for DPO / GRPO training, **Export merged (DPO)** (tab 7c), **Eval red team** (tab 5b); `export_merged.py` uses `ProfileConfig.max_seq_len` for L40 stability.
- **Local GGUF:** document pinning `gguf-py` to the same git SHA as Homebrew `llama.cpp` (avoids `HUNYUAN_VL` / `MODEL_ARCH` mismatch with `convert_hf_to_gguf.py`).
- **GEPA / DSPy:** `scripts/dspy/gepa_system_prompt.py`, `data/optimized_system_prompt.json` (bootstrap run, devset metric).

## Intended Purpose

- Intended domain: questions about Deal ex Machina services, content, and related company context.
- Intended users: website visitors and authenticated users, depending on profile routing in production.
- Intended geographies/languages: French and English.

## Out-of-Scope Use

- General-purpose assistant usage unrelated to Deal ex Machina.
- Legal, medical, financial, hiring, credit, insurance, law-enforcement, or other high-impact decisions.
- Any use requiring guaranteed factual completeness.

## AI Act Transparency (Article 50) Notes

- This model powers a chatbot experience where users are informed they interact with AI.
- System scope is limited-risk as deployed (not categorized as high-risk use under current deployment assumptions).
- Human oversight remains with product operators; model output should not be used as sole basis for consequential decisions.

## Data and Training Provenance

- Base model: `LiquidAI/LFM2-24B-A2B`
- Training track: `sft`
- Fine-tuning method: LoRA SFT (see project pipeline)
- Approximate SFT dataset size: 909 examples
- Dataset metadata snapshot version: `0.3.4`
- Data policy: no direct end-user chat logs are used for SFT

## Evaluation, Robustness, and Safety

- Report: `reports/redteam/v0.3.5/auth_redteam_20260427-232807.md`
- Evaluated at (UTC): `2026-04-27T23:28:07Z`
- Release gate: **FAIL** (pass rate `70.8%`, failures `7`)

## Known Limitations

- Domain-bounded assistant; degraded quality outside scope.
- Non-zero hallucination risk for edge prompts.
- Safety/robustness tests are finite and release-based.

## Risk Management and Incident Process

- Document escalation path for harmful/incorrect outputs.
- Link internal release gate evidence and retention policy.
- TODO: add public contact route for reporting model issues.

## License and Redistribution

- SPDX field: `other`
- License note: LFM Open License v1.0 (Liquid AI)
- Derivative distribution must comply with upstream model terms and Hugging Face terms.

## Maintainer Update Checklist

- [ ] Version/changelog links updated
- [ ] Dataset counts refreshed from `data/metadata.json`
- [ ] Latest red-team report attached or linked
- [ ] Limitations and out-of-scope section reviewed
- [ ] AI Act transparency language reviewed against current product behavior
- [ ] License section validated for this base model family