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GRPOTrainer, r32/α64) on the merged SFT model, with the live
GPTZero detector in the reward (reward = gate × (1 − aiProb)), KL-anchored to the SFT
reference and gated against reward-hacking (length floor, n-gram repetition, perplexity
gibberish guard). 100 steps.group_size 64, affine).| Model | median AI % | <15% (held-out) |
|---|---|---|
| Base Qwen3-14B | 100% | 0/24 |
| + SFT on the author's corpus | 5% | 16/25 |
| + GRPO vs. live GPTZero (this model) | 3% | 18/25 |
1pip install mlx-lm
2python -m mlx_lm chat --model ericlmtn/qwen3-14b-personal-voice-mlx
3# or, generate:
4python -m mlx_lm generate --model ericlmtn/qwen3-14b-personal-voice-mlx \
5 --prompt "Rewrite this paragraph in my voice: ..." --max-tokens 400