Instructions to use jeanbaptdzd/wagmi-qwen3-0.6b-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jeanbaptdzd/wagmi-qwen3-0.6b-sft with PEFT:
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File size: 3,556 Bytes
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language:
- en
- fr
license: apache-2.0
base_model: unsloth/Qwen3-0.6B
library_name: peft
pipeline_tag: text-generation
tags:
- wagmi
- deal-ex-machina
- sft
- qwen3
- small
- adapter
---
# Wagmi (qwen3/small/sft) - adapter
**Version:** 0.3.5
**Repo ID:** `jeanbaptdzd/wagmi-qwen3-0.6b-sft`
## Model Summary
This model is part of the Wagmi assistant stack for Deal ex Machina. It is a `adapter` artifact in the `qwen3` family (`small` 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: `unsloth/Qwen3-0.6B`
- 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
- Latest release red-team report for this family/profile is not available.
- Add a linked report before publishing a production-facing card.
## 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: `apache-2.0`
- License note: Apache 2.0 (Qwen base model)
- 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
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