anthonym21/qwen3-0.6b-rlcd-decision

text-classification model by anthonym21

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A decision-only model: it reads one state and a list of typed questions, runs one forward pass, and returns a probability distribution over the options each question declares. It does not generate text. It is Qwen3-0.6B-Base after a short supervised warmup and 500 steps of reinforcement learning for calibrated decisions (RLCD), a REINFORCE loop under bandit feedback whose reward is the outcome minus the probability the model put on the option it chose. On the held-out test split it is as calibrated as the warmup it started from (ECE 0.021) and six accuracy points better (0.807 against 0.746); the same loop with a plain outcome reward ends at ECE 0.216 or worse. Code, training, evaluation and the loader live at github.com/anthony-maio/eve-rlcd. This repository is the export of runs/q-rlcd from that project, and it needs the rlcd package from that repository to load; it is not a stock transformers checkpoint with…

anthonym21/qwen3-0.6b-rlcd-decision on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. Qwen3-0.6B RLCD decision model
  2. What is in the repository
  3. The three primitives
  4. How it was trained
  5. Results
  6. Known-posterior probe
  7. Limitations
  8. Intended use and out-of-scope use
  9. Reproduce
  10. Credits
  11. Citation

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Model overview

anthonym21/qwen3-0.6b-rlcd-decision is a text-classification model repository published by anthonym21 on Hugging Face. A library was not reported.

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Model facts

Task
text-classification
Library
Not reported
Recent downloads (30 days)
0
Cumulative likes
0
Hugging Face trending score
0
Reported safetensors parameters
596,049,920
Architecture
Qwen3Model
License
apache-2.0
Access
Not gated by Hugging Face
Created
2026-09-19T06:15:20.000Z
Last modified
2026-09-19T06:22:52.000Z

Compatibility and lineage

Reported languages: en

Reported base models: Qwen/Qwen3-0.6B-Base

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.

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Model card and usage instructions

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Source: Hugging Face Hub. Metadata observed 2026-09-19T06:35:16.985Z. Daily imports are snapshots, not real-time monitoring.

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