---
base_model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
library_name: peft
pipeline_tag: text-generation
tags:
- base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Llama-8B
- lora
- sft
- transformers
- trl
---

# Model Card for Model ID

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## Model Details

### Model Description

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- **Developed by:** [More Information Needed]
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- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]

### Model Sources [optional]

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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

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### Direct Use

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### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data

The model was trained using the ThinkSafe self-generated safety alignment methodology. See the paper for details on the training data generation process.

### Training Procedure

This model uses LoRA (Low-Rank Adaptation) for efficient fine-tuning on top of the Qwen3-0.6B base model. The training follows the ThinkSafe framework for safety alignment in reasoning models.

#### Training Hyperparameters

- **Training regime:** Mixed precision training with PEFT/LoRA

## Evaluation

Please refer to the [ThinkSafe paper](https://huggingface.co/papers/2601.23143) for detailed evaluation results and methodology.

### Testing Data, Factors & Metrics

#### Testing Data

See the paper for details on evaluation datasets and benchmarks used.

#### Metrics

The model was evaluated on safety benchmarks and reasoning tasks. Refer to the paper for specific metrics and results.

## Environmental Impact

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

## Citation

**BibTeX:**

```bibtex
@article{lee2025thinksafe,
  title={THINKSAFE: Self-Generated Safety Alignment for Reasoning Models},
  author={Lee, Seanie and others},
  journal={arXiv preprint arXiv:2601.23143},
  year={2025}
}
```

## More Information

For more details, please refer to:
- Paper: https://huggingface.co/papers/2601.23143
- GitHub Repository: https://github.com/seanie12/ThinkSafe.git


## Model Card Authors [optional]

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## Model Card Contact

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### Framework versions

- PEFT 0.18.1