---
base_model: unsloth/DeepSeek-R1-Distill-Qwen-7B-unsloth-bnb-4bit
library_name: transformers
license: apache-2.0
datasets:
- leonvanbokhorst/friction-uncertainty-v2
language:
- en
tags:
- ai-safety
- ai-friction
- human-like-messiness
- ai-uncertainty
pipeline_tag: text-generation
---

# Friction Reasoning Model

This model is fine-tuned to respond in an uncertain manner. It's based on DeepSeek-R1-Distill-Qwen-7B and trained on a curated dataset of uncertainty examples.

## Model Description

- **Model Architecture**: DeepSeek-R1-Distill-Qwen-7B with LoRA adapters
- **Language(s)**: English
- **License**: Apache 2.0
- **Finetuning Approach**: Instruction tuning with friction-based reasoning examples


### Limitations

The model:
- Is not designed for factual question-answering
- May sometimes be overly uncertain
- Should not be used for medical, legal, or financial advice
- May not perform well on objective or factual tasks

### Bias and Risks

The model:
- May exhibit biases present in the training data
- Could potentially reinforce uncertainty in certain situations
- Might challenge user assumptions in sensitive contexts
- Should be used with appropriate content warnings




## Citation

If you use this model in your research, please cite:

```bibtex
@misc{friction-reasoning-2025,
  author = {Leon van Bokhorst},
  title = {Mixture of Friction: Fine-tuned Language Model for Uncertainty},
  year = {2025},
  publisher = {HuggingFace},
  journal = {HuggingFace Model Hub},
  howpublished = {\url{https://huggingface.co/leonvanbokhorst/deepseek-r1-uncertainty}}
}
```

## Acknowledgments

- DeepSeek AI for the base model
- Unsloth team for the optimization toolkit
- HuggingFace for the model hosting and infrastructure