| library_name: transformers | |
| license: apache-2.0 | |
| base_model: Qwen/Qwen3.5-9B | |
| tags: | |
| - harness-engineering | |
| - agent | |
| - supervised-fine-tuning | |
| - reinforcement-learning | |
| # Harness-R1 | |
| Model artifacts for Harness-R1 experiments. The repository separates the | |
| target agent from the Harness Engineer so that the two roles are not confused. | |
| | Directory | Role | | |
| |---|---| | |
| | `cold-start-sft/` | Supervised-only Harness Engineer (SFT/0), used to initialize E0 RL | | |
| | `harness-r1/` | E0 Harness Engineer for the vanilla A0 target agent | | |
| | `agent-sft-harness-r1/` | E1 Harness Engineer conditioned on A1 trajectories | | |
| | `target-agent-sft/` | Direct Agent-SFT target model (A1), not a Harness Engineer | | |
| ## Loading | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| repo = "ShaoShuai0605/Harness-R1" | |
| subfolder = "harness-r1" # Or cold-start-sft / agent-sft-harness-r1 / target-agent-sft | |
| tokenizer = AutoTokenizer.from_pretrained( | |
| repo, | |
| subfolder=subfolder, | |
| trust_remote_code=True, | |
| ) | |
| model = AutoModelForCausalLM.from_pretrained( | |
| repo, | |
| subfolder=subfolder, | |
| trust_remote_code=True, | |
| ) | |
| ``` | |
| See the README inside each directory for its intended role. | |