Question Answering
Transformers
Safetensors
English
qwen3
text-generation
rule-based reasoning
text-generation-inference
Instructions to use RuleReasoner/RuleReasoner-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RuleReasoner/RuleReasoner-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="RuleReasoner/RuleReasoner-8B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("RuleReasoner/RuleReasoner-8B") model = AutoModelForCausalLM.from_pretrained("RuleReasoner/RuleReasoner-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
datasets:
- RuleReasoner/rule-reasoning
language:
- en
base_model:
- Qwen/Qwen3-8B-Base
pipeline_tag: question-answering
library_name: transformers
tags:
- rule-based reasoning
Citation
If you use the model in your research, please cite the original papers as below.
@article{liu2025rulereasoner,
title={RuleReasoner: Reinforced Rule-based Reasoning via Domain-aware Dynamic Sampling},
author={Yang Liu and Jiaqi Li and Zilong Zheng},
year={2025},
eprint={2506.08672},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2506.08672},
}