Instructions to use ShaoShuai0605/Harness-R1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShaoShuai0605/Harness-R1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ShaoShuai0605/Harness-R1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| library_name: transformers | |
| base_model: Qwen/Qwen3.5-9B | |
| tags: | |
| - harness-r1 | |
| - agent | |
| - reinforcement-learning | |
| # Harness-R1 | |
| Harness-engineer checkpoints from the paper main table. | |
| | Subfolder | Paper row | | |
| |---|---| | |
| | [`harness-r1`](./harness-r1) | Harness-R1 | | |
| | [`agent-sft-harness-r1`](./agent-sft-harness-r1) | Agent SFT + Harness-R1 | | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| repo = "ShaoShuai0605/Harness-R1" | |
| subfolder = "harness-r1" # or agent-sft-harness-r1 | |
| tok = AutoTokenizer.from_pretrained(repo, subfolder=subfolder, trust_remote_code=True) | |
| model = AutoModelForCausalLM.from_pretrained(repo, subfolder=subfolder, trust_remote_code=True) | |
| ``` | |