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--- |
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base_model: unsloth/deepseek-r1-distill-qwen-32b |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- qwen2 |
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- trl |
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license: apache-2.0 |
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language: |
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- en |
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datasets: |
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- Daemontatox/math_conv |
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library_name: transformers |
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--- |
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# Zirel-R1: Optimized for Fast and Essential Reasoning |
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## Model Overview |
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**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. |
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- **Developed by:** Daemontatox |
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- **Model Series:** Zirel |
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- **Base Model:** `unsloth/deepseek-r1-distill-qwen-32b` |
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- **License:** Apache-2.0 |
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- **Languages:** English |
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- **Finetuned on:** `Daemontatox/math_conv` |
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- **Library:** Transformers |
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## Key Features |
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✅ **Fast and Concise Reasoning** – Delivers precise answers with minimal computational overhead. |
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✅ **Optimized for Short-Form Problem Solving** – Excels in extracting core insights efficiently. |
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✅ **Enhanced Logical Inference** – Ideal for applications in structured decision-making, math reasoning, and controlled AI workflows. |
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## Usage |
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You can load the model using `transformers`: |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_name = "Daemontatox/Zirel-R1" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto") |
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prompt = "What is the next number in the sequence: 2, 4, 8, 16?" |
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda") |
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output = model.generate(**inputs, max_new_tokens=50) |
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print(tokenizer.decode(output[0], skip_special_tokens=True)) |
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Performance |
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Speed: 🚀 Optimized for rapid inference and low-latency responses. |
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Accuracy: 🎯 Fine-tuned on high-quality mathematical and reasoning datasets. |
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Efficiency: ⚡ Processes only the necessary information for an answer. |
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Citation |
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If you use Zirel-R1, please cite: |
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@misc{daemontatox2025zirel, |
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author = {Daemontatox}, |
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title = {Zirel-R1: Optimized for Fast and Essential Reasoning}, |
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year = {2025}, |
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publisher = {Hugging Face}, |
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url = {https://huggingface.co/Daemontatox/Zirel-R1} |
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} |
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License |
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This model is released under the Apache-2.0 License. |
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--- |
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