TaskWizerAI/opencodifier-e1e-2b
text-generation model by TaskWizerAI
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Model card & documentation
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A LoRA adapter that turns Qwen/Qwen3.5-2B into a Jev-style decision model: probabilities are read from the log-probs of verdict-slot label tokens at the answer position — nothing is generated, nothing is parsed. It is the decision rung of the OpenCodifier ladder, and the first own-trained arm to pass both release-gate legs. All numbers from the OpenCodifier evaluation records (BENCHMARKS.md, TRAINING.md §9.9.1). Public 231-item JevBench split, deterministic readout, fp16, single V100. Per-family shape: routing / tool-selection / ordinal families at 1.00; relational/compositional families are the weakness (multihop 0.389, judgehard 0.412, longpolicy 0.368). The board is lost on compositional families, not on routing — the candidate lever is relational-heavy soft-label data, not parameters. TRAINING.md). The corpus itself is not released with this adapter. (holdout ECE 0.179 → 0.117); artifact ships in the OpenCodifier repo at calibration/e1e-qwen3.5-2b-holdout.json Typed multiple-choice decisions…
Read the full model card ↗ · Preview checked 2026-10-31T03:28:14.059Z
Inside the original model card — Document outline
- OpenCodifier E1-E — Qwen3.5-2B verdict-slot decision LoRA
- Results
- Training
- Intended use
- Out of scope
- How to use
- License
- Citation
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Model overview
TaskWizerAI/opencodifier-e1e-2b is a text-generation model repository published by TaskWizerAI on Hugging Face. The source reports the peft library.
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Model facts
- Task
- text-generation
- Library
- peft
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-26T06:08:17.000Z
- Last modified
- 2026-10-26T06:09:11.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: Qwen/Qwen3.5-2B
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-26T06:47:05.388Z. Daily imports are snapshots, not real-time monitoring.
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