---
license: apache-2.0
base_model:
- deepseek-ai/DeepSeek-R1-Zero
datasets:
- Daemontatox/Reasoning_am
- pbcong/gsm8k_step_by_step
- Daemontatox/Deepthinking-COT
- Daemontatox/Qwqloncotam
language:
- en
library_name: transformers
tags:
- wip
- experimental
- moe
- finetune
- research
pipeline_tag: text-generation
metrics:
- accuracy
- code_eval
---
![image](./image.webp)

# Z1: Experimental Fine-Tune of R1-Zero

**Z1** is a highly experimental fine-tune of the **DeepSeek-R1-Zero** model, designed for research purposes and not intended for production use. This model focuses on advancing reasoning capabilities and structured inference through fine-tuning on multiple high-quality reasoning datasets.

---

## Key Features

- **Experimental Fine-Tune**: Z1 is a research-oriented fine-tune of state-of-the-art large language models, aimed at exploring advanced reasoning and inference techniques.  
- **Research-Only Use Case**: This model is not suitable for production environments and is intended solely for experimental and academic purposes.  
- **Enhanced Reasoning Abilities**: Fine-tuned on diverse reasoning datasets to improve logical inference, step-by-step problem-solving, and structured reasoning.  
- **Chain-of-Thought (CoT) Focus**: Optimized for multi-step reasoning tasks, leveraging Chain-of-Thought learning to enhance structured and interpretable inference.  

---

## Intended Use

Z1 is designed for researchers and developers exploring the following areas:  
- **Reasoning and Inference**: Evaluating and improving logical reasoning, step-by-step problem-solving, and structured inference in language models.  
- **Chain-of-Thought Learning**: Investigating the effectiveness of CoT techniques in enhancing multi-step reasoning.  
- **Experimental Fine-Tuning**: Studying the impact of fine-tuning on specialized datasets for improving model performance in specific domains.  

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## Limitations

- **Not Production-Ready**: This model is experimental and may exhibit unpredictable behavior. It should not be used in production systems.  
- **Uncensored Outputs**: As an uncensored model, Z1 may generate content that is inappropriate or unsafe without additional safeguards.  
- **Work in Progress**: The model is still under development, and its performance may vary across tasks and datasets.  

---

## Datasets Used for Fine-Tuning

1. **Reasoning_am**: Focused on advanced reasoning tasks.  
2. **gsm8k_step_by_step**: A dataset emphasizing step-by-step problem-solving in mathematical reasoning.  
3. **Deepthinking-COT**: Designed to enhance Chain-of-Thought reasoning capabilities.  
4. **Qwqloncotam**: A specialized dataset for improving structured inference and multi-step reasoning.  

---

## Ethical Considerations

- **Responsible Use**: This model is intended for research purposes only. Users should ensure that its outputs are carefully monitored and evaluated.  
- **Bias and Fairness**: As with all language models, Z1 may inherit biases from its training data. Researchers should assess and mitigate potential biases in their applications.  
- **Safety**: Due to its uncensored nature, additional safeguards may be required to prevent misuse or harmful outputs.  

---

## Future Work

- **Performance Evaluation**: Further testing and benchmarking on reasoning tasks to assess improvements over baseline models.  
- **Dataset Expansion**: Incorporating additional datasets to enhance reasoning and inference capabilities.  
- **Safety and Alignment**: Exploring methods to align the model with ethical guidelines and safety standards for broader use.