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
File size: 719 Bytes
0e26bf9 2b06337 0e26bf9 2b06337 0e26bf9 2b06337 c1ae038 0e26bf9 c1ae038 2b06337 0e26bf9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ---
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)
```
|