Text Generation
PEFT
Safetensors
English
lora
alignment
criterion-following
sycophancy
mrf-v2
conversational
Instructions to use rafalwronapl/qwen3-14b-no-think-mrf-sft-t5-t6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rafalwronapl/qwen3-14b-no-think-mrf-sft-t5-t6 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B") model = PeftModel.from_pretrained(base_model, "rafalwronapl/qwen3-14b-no-think-mrf-sft-t5-t6") - Notebooks
- Google Colab
- Kaggle
Qwen3-14B no-think MRF SFT (T5+T6 faithful replacements)
LoRA adapter for Qwen/Qwen3-14B in /no_think mode, trained on the MRF v2
T5+T6 faithful-replacement set. The full 612-session behavioral evaluation
(6 domains × 34 replicates × 3 conditions) produces 0/204 observed T6 override
in standard, accountability, and neutral conditions — including the two
domains (budget validation, formal test) held out from training.
Part of the MRF v2 release. See the GitHub repository for code, the small MRF-Bench v0.1 benchmark, the full paper outline, and the parser-validation appendix. See the Zenodo deposit for the raw 3,872 base-model sessions and this run's 612-session held-out evaluation.
License: Apache 2.0.
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