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README.md
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---
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base_model:
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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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- qwen3
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license: apache-2.0
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language:
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- en
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---
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- **Developed by:** Ali-Yaser
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- **
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---
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base_model:
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- Qwen/Qwen3-8B
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tags:
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- transformers
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- qwen3
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- R1
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- THİNK
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license: apache-2.0
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language:
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- en
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---
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[<img src="https://i.imgur.com/vo0dm9p.jpeg" width="710"/>]()
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# Qwen3-R1 8B 🚀
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<div align="center">
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[](https://huggingface.co/Ali-Yaser/Qwen3-R1-8B)
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[](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md)
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[](https://huggingface.co/Qwen/Qwen3-8B)
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</div>
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## Model Description
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**Qwen3-R1 Series** is a specialized math and reansoning awnsers-focused fine-tuned version of Qwen3-8B Instruct, optimized for Math and hard question tasks.
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## 📊 Model Details
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- **Developed by:** Ali-Yaser
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- **Model type:** GRPO thinker
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- **Base Model:** Qwen/Qwen3-8B
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- **Model Size:** 8B parameters
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- **License:** Apache 2.0
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- **Language(s):** English
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- **Finetuned from:** Qwen3-8B
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## 🚀 Quick Start
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### Installation
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I use a vLLM
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```
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# Install vLLM from pip:
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pip install vllm
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```
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and lets download the model and run model
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```python
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# Load and run the model:
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vllm serve "Ali-Yaser/Qwen3-R1-8B"
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```
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and Run it this is example
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#
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```
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# Call the server using curl:
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curl -X POST "http://localhost:8000/v1/chat/completions" \
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-H "Content-Type: application/json" \
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--data '{
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"model": "Ali-Yaser/Qwen3-R1-8B",
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"messages": [
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{
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"role": "user",
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"content": "1+434334434+10x22=?"
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}
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]
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}'
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```
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