初始化项目，由ModelHub XC社区提供模型

Model: steven0226/qwen2.5-1.5b-wordle-grpo-merged
Source: Original Platform

README.md

@@ -0,0 +1,84 @@
+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+pipeline_tag: text-generation
+tags:
+- reinforcement-learning
+- grpo
+- agentic-rl
+- multi-turn
+- wordle
+- merged-model
+language:
+- en
+---
+
+# Qwen2.5-1.5B Wordle GRPO merged full model
+
+## Repository role
+
+This repository contains the historical **merged full model** counterpart of the Wordle GRPO
+LoRA adapter. It does not require a separately attached LoRA adapter for loading. The base
+repository identity is `Qwen/Qwen2.5-1.5B-Instruct`; the current `model.safetensors` LFS SHA-256 is
+`b6c55086e798e1f62e6d970f07ee97ab39c1e0af3ee4b6ecdb2a349e485087af`.
+
+The repository relationship is supported by historical documentation, subject to the lineage
+limits below. It is not a cryptographically complete adapter-to-merged derivation record.
+
+## Evaluation
+
+The published 463-word result originates from the adapter evaluation. No independent 463-word evaluation was run against these merged bytes, so the adapter result is not an independent replication of merged-model performance. The aggregate adapter result is included here only to
+document the paired project evidence without inventing a separate merged-model result.
+
+| Measure | Base | Tuned LoRA adapter evidence |
+|---|---:|---:|
+| Wins | 0/463 | 13/463 = 2.81% |
+| Wilson 95% CI | 0.00%–0.82% | 1.65%–4.74% |
+| Protocol adherence | 0% | 2749/2753 = 99.85% |
+| Legal actions | 0% | 2748/2753 = 99.82% |
+
+The paired discordance was 0 base-only wins and 13 tuned-only wins. The two-sided exact paired
+McNemar result is `0.000244140625`; treating the interim and final evaluations as two looks gives
+the conservative Bonferroni-adjusted value `0.00048828125`.
+
+The adapter evaluation also recorded 1340/2290 absent-letter reuses and 1119/2290 broken green
+positions on turns with information.
+
+**Protocol learning succeeded; strategy learning remained limited; this is not a practical Wordle solver.** The 2.81% adapter win rate must not be presented as an independently measured
+merged-model win rate, practical capability, or general RL superiority.
+
+## Evidence links
+
+- Immutable research/evidence source:
+  https://github.com/kuotunyu/agentic-rl-wordle/commit/1a077a45e309594e5bb43743a8b84d89155595d4
+- Stable source release URL:
+  https://github.com/kuotunyu/agentic-rl-wordle/releases/tag/v1.0.0
+- Aggregate report: `results/full_463_report.json`
+- Recomputed analysis: `results/full_463_analysis.json`
+- Public claim mapping: `docs/claim-matrix.md`
+
+## Limitations
+
+- Only aggregate 463-game evidence is committed; full per-episode records are unavailable.
+- The historical GPU environment is not bit-for-bit reconstructable.
+- The exact upstream Qwen commit was not preserved.
+- The adapter-to-merged command and manifest were not preserved, and the historical record lacks
+  an end-to-end run→code→prompt→bundle→model cryptographic chain. The relationship is documentary lineage, not complete cryptographic proof.
+- The cfreshman word lists are fetch-only and have no explicit license. Apache-2.0 does not license the cfreshman word lists.
+- Representative transcripts are illustrations, not a complete raw evaluation corpus.
+- No independent evaluation of these merged bytes is available; do not infer byte-level
+  equivalence or independently replicated performance from the documentary relationship.
+
+## Loading
+
+This repository is intended to load as a full causal language model and does not need a separate
+PEFT adapter attachment. Because the exact historical upstream base revision and merge manifest
+are unavailable, do not claim a complete cryptographic reconstruction of the merge.
+
+```python
+from transformers import AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained(
+    "steven0226/qwen2.5-1.5b-wordle-grpo-merged"
+)
+```