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weft-lineage-extractor-0.5b
wallfacers/weft-lineage-extractor-0.5b
weft-lineage-extractor-0.5b is a text generation model from wallfacers. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
⚠️ RESEARCH ARTIFACT — the 0.5B point of a synthetic-only training study. Not a production tool. ✅ Resolved by real data: use weft-lineage-extractor-3b (real corpus, real precision 0.64). Full study: weft-lineage-extr…
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At a glance
- Task
- Text Generation
- Library
- transformers
- License
- other
- Model type
- qwen2
- Access
- Public
- Created
- Jul 5, 2026
- Updated
- Jul 10, 2026
- SHA
- 2b929c43
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Base models
Model card
From the Hugging Face model README
weft-lineage-extractor-0.5b — smallest scale point of a NEGATIVE RESULT
⚠️ RESEARCH ARTIFACT — the 0.5B point of a synthetic-only training study. Not a production tool.
✅ Resolved by real data: use weft-lineage-extractor-3b (real corpus, real precision 0.64). Full study: weft-lineage-extractor-1.5b.
The 0.5B point of a study showing that synthetic-only training induces a verbatim memorization leak in small models for ETL table-lineage extraction. It is the smallest scale point and shows the worst leak: near-perfect synthetic precision (0.994) collapses to 0.243 on real GitHub scripts, with 37.4% of hallucinations being table names recited verbatim from the synthetic training pool.
Same recipe as the 1.5B main model (LoRA on Qwen2.5-Coder-Instruct, Python/Shell synthetic ETL scripts, zero real scripts); only the base size differs.
This point's numbers (table-level, Convention A)
| metric | synthetic held-out | real GitHub ETL |
|---|---|---|
| precision | 0.994 | 0.243 |
| direction accuracy | — | 0.369 |
| verbatim memorization leak | — | 37.4% |
Where it fits (scale curve)
| scale | real precision | real direction | verbatim leak |
|---|---|---|---|
| 0.5B (this) | 0.243 | 0.369 | 37.4% |
| 1.5B (main) | 0.270 | 0.496 | 22.4% |
| 3B (synthetic) | 0.325 | 0.468 | 10.9% |
| 3B (real corpus) | 0.64 | — | ~0 |
Leak shrinks with scale (capacity), but only real training data closes the real-world gap (bottom row). Direction confusion does not improve with size.
Intended use
- ✅ Reproducing / studying the synthetic-training memorization-leak failure at minimal scale.
- ❌ Not for production lineage — use the real-corpus 3B.
Usage, prompt format, training details, citation
Identical to the main model (this variant uses task_type: PYTHON | SHELL; everything else the same):
weft-lineage-extractor-1.5b.
- Dataset & reports: wallfacers/weft-script-lineage-synth
- Base model: Qwen/Qwen2.5-Coder-0.5B-Instruct
- Platform: Weft (data-weave)
- Task
- Text Generation
- Library
- transformers
- Type
- qwen2
- License
- other
- Languages
- en
- Created
- Jul 5, 2026
- Updated
- Jul 10, 2026