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Model: laion/rl_pymethods2test-r2egym_terminus-structured
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: laion/r2egym-nl2bash-stack-bugsseq-fixthink-again
+tags:
+  - reinforcement-learning
+  - code
+  - pymethods2test
+  - r2egym
+  - rl
+  - rloo-n
+  - terminus-structured
+language:
+  - en
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# rl_pymethods2test-r2egym_terminus-structured
+
+RL-trained Qwen3-8B with structured tool calls (terminus-structured agent).
+
+## Training Pipeline
+
+SFT (r2egym+nl2bash+swesmith) → RL mixed dataset (37 steps) → RL full r2egym (55 steps) → RL pymethods2test (156 steps, full epoch)
+
+## Key Results
+
+- **SWEBench-100 pass@3**: 37-42% (depending on eval run)
+- **Pymethods2test pass@8**: 91-97%
+- **SWEBench in-train eval**: up to 14 fully solved at various checkpoints
+- Training on test-writing (pymethods) maintains code-editing ability (SWEBench)
+
+## Training Details
+
+- **Base model**: [laion/r2egym-nl2bash-stack-bugsseq-fixthink-again](https://huggingface.co/laion/r2egym-nl2bash-stack-bugsseq-fixthink-again)
+- **Agent**: terminus-structured (bash, view, edit, create, search tools)
+- **Algorithm**: RLOO-N
+- **Learning rate**: 1e-5
+- **Context**: 32k (24k input + 8k output)
+- **Framework**: BenSkyRL + Harbor (JSC HPC)
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("laion/rl_pymethods2test-r2egym_terminus-structured")
+tokenizer = AutoTokenizer.from_pretrained("laion/rl_pymethods2test-r2egym_terminus-structured")
+```