47c380e84ab0fbe92d4eccaf03ab8df3816368ce
Model: metacognitive-behavioral-tuning/Qwen3-0.6B-MBT-R Source: Original Platform
base_model, language, library_name, license, pipeline_tag, tags
| base_model | language | library_name | license | pipeline_tag | tags | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Qwen/Qwen3-0.6B |
|
transformers | apache-2.0 | text-generation |
|
Qwen3-0.6B · MBT-R
MBT-R (main table) — final checkpoint (SFT → GRPO). Base: Qwen/Qwen3-0.6B.
Paper: Metacognitive Behavioral Tuning of Large Language Models for Multi-Hop Question Answering.
- Method: MBT-R (Refinement): the student's own reasoning traces are rewritten into the 5-phase structure for SFT, then GRPO.
- Base model:
Qwen/Qwen3-0.6B - Training: SFT (LR 1e-4, BS 128, HotpotQA) → GRPO
- Benchmarks: HotpotQA (ID), MuSiQue / 2WikiMultiHopQA (OOD)
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "metacognitive-behavioral-tuning/Qwen3-0.6B-MBT-R"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(repo, dtype="bfloat16", device_map="auto")
Description
Languages
Jinja
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