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") - Notebooks
- Google Colab
- Kaggle
Improve model card (pipeline tag, add Github link)
Browse filesThis PR improves the model card by changing the pipeline tag to `text-generation` to improve discoverability. It also adds a link to the Github repository for the project.
README.md
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---
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-
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datasets:
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- RuleReasoner/rule-reasoning
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language:
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- en
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base_model:
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- Qwen/Qwen3-8B-Base
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pipeline_tag: question-answering
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library_name: transformers
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tags:
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- rule-based reasoning
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---
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2506.08672},
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}
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```
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---
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base_model:
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- Qwen/Qwen3-8B-Base
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datasets:
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- RuleReasoner/rule-reasoning
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language:
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- en
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library_name: transformers
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license: mit
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pipeline_tag: text-generation
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tags:
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- rule-based reasoning
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---
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2506.08672},
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}
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```
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Code: https://github.com/bigai-nlco/RuleReasoner
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