---
base_model: unsloth/deepseek-r1-distill-qwen-32b
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- trl
license: apache-2.0
language:
- en
datasets:
- Daemontatox/math_conv
library_name: transformers
---

# Zirel-R1: Optimized for Fast and Essential Reasoning

![Zirel Logo](./image.webp)

## Model Overview

**Zirel-R1** is an advanced **reasoning-optimized** model designed for **short, fast, and necessary reasoning**, avoiding long and unnecessary computation. It surpasses **Cogito-R1** and **PathfinderAI S1** in efficiency, making it ideal for applications requiring structured logical inference and quick decision-making.

- **Developed by:** Daemontatox 
- **Model Series:** Zirel  
- **Base Model:** `unsloth/deepseek-r1-distill-qwen-32b`  
- **License:** Apache-2.0  
- **Languages:** English  
- **Finetuned on:** `Daemontatox/math_conv`  
- **Library:** Transformers  

## Key Features

✅ **Fast and Concise Reasoning** – Delivers precise answers with minimal computational overhead.  
✅ **Optimized for Short-Form Problem Solving** – Excels in extracting core insights efficiently.  
✅ **Enhanced Logical Inference** – Ideal for applications in structured decision-making, math reasoning, and controlled AI workflows.  

## Usage

You can load the model using `transformers`:

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "Daemontatox/Zirel-R1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")

prompt = "What is the next number in the sequence: 2, 4, 8, 16?"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
output = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(output[0], skip_special_tokens=True))

Performance

Speed: 🚀 Optimized for rapid inference and low-latency responses.

Accuracy: 🎯 Fine-tuned on high-quality mathematical and reasoning datasets.

Efficiency: ⚡ Processes only the necessary information for an answer.


Citation

If you use Zirel-R1, please cite:

@misc{daemontatox2025zirel,
  author = {Daemontatox},
  title = {Zirel-R1: Optimized for Fast and Essential Reasoning},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co./Daemontatox/Zirel-R1}
}

License

This model is released under the Apache-2.0 License.


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