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Model: laion/rl_r2egym-full_terminus-structured
Source: Original Platform

README.md

@@ -0,0 +1,45 @@
+---
+license: apache-2.0
+base_model: laion/r2egym-nl2bash-stack-bugsseq-fixthink-again
+tags:
+  - reinforcement-learning
+  - code
+  - r2egym
+  - rl
+  - rloo-n
+  - terminus-structured
+language:
+  - en
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# rl_r2egym-full_terminus-structured
+
+RL-trained Qwen3-8B with structured tool calls. Continued from mixed step 37 with full r2egym dataset (1785 tasks) for 18 more steps.
+
+SWEBench-100: 42% pass@3. Training pass@8 peaked at 90.6%.
+
+## Training Details
+
+- **Base model**: [laion/r2egym-nl2bash-stack-bugsseq-fixthink-again](https://huggingface.co/laion/r2egym-nl2bash-stack-bugsseq-fixthink-again)
+- **Training method**: rloo-n with terminus-structured agent (structured tool calls: bash, view, edit, create, search)
+- **Framework**: BenSkyRL + Harbor 
+- **Context**: 32k (24k input + 8k output)
+- **Learning rate**: 1e-5
+
+## SWEBench-Verified Results (100 tasks, pass@3)
+
+| Model | SWEBench pass@3 |
+|---|---|
+| Base SFT (terminus-2) | 37% |
+| This model (terminus-structured) | See eval results |
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("laion/rl_r2egym-full_terminus-structured")
+tokenizer = AutoTokenizer.from_pretrained("laion/rl_r2egym-full_terminus-structured")
+```