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everscending/qwen3-1.7b-article-usage-micro-coach
qwen3-1.7b-article-usage-micro-coach is a text generation model from everscending. Use it when you need the model to write or continue text. It is set up for mlx. The card lists the license as apache-2.0.
This is a dequantized MLX fusion of a QLoRA adapter trained from mlx-community/Qwen3-1.7B-4bit. It asks one conceptual coaching question about one English article error without revealing the correction. After the lear…
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From the Hugging Face model README
This is a dequantized MLX fusion of a QLoRA adapter trained from
mlx-community/Qwen3-1.7B-4bit. It asks one conceptual coaching question about
one English article error without revealing the correction. After the learner
independently fixes the target, it responds exactly Target fixed.
3b1b1768f8f8cf8351c712464f906e86c2b8269e| Model | Spec adherence | Robustness | Mean usefulness |
|---|---|---|---|
| Untuned Qwen3 | 1/60 (1.7%) | 1/30 (3.3%) | 0.100 |
| Dataset v2 adapter | 43/60 (71.7%) | 23/30 (76.7%) | 1.433 |
Before upload, this dequantized fusion reproduced the adapter's pass pattern on a five-case semantic parity check: 4/5 passes and 1.600 usefulness. The remaining failure was the same known wrong-concept case as the adapter.
This model is not reliable enough for unsupervised teaching. Its largest remaining failure is asking a well-formed question about the wrong article rule.
Use evaluation-code commit
a413040a6177921a5e770f6c71203b4f812e728f:
python eval.py \
--model everscending/qwen3-1.7b-article-usage-micro-coach \
--eval-set eval/scenarios/dev.jsonl