---
title: ReasoningV-7B
canonical_url: "https://www.modelscope.cn/models/GipsyAI/ReasoningV-7B"
md_url: "https://www.modelscope.cn/models/GipsyAI/ReasoningV-7B.md"
repository: GipsyAI/ReasoningV-7B
chinese_name: ReasoningV-7B
last_updated: 2025-10-12
model_type:
  - qwen2
architectures:
  - Qwen2ForCausalLM
parameters: 7.6B
tensor_type:
  - F32
library_name:
  - safetensors
inference_backends:
  - "deploy_task text/emb"
  - "lmdeploy 0.9.1"
  - "lmdeploy_turbomind 0.9.1"
  - "sglang 0.5.2"
  - "vllm 0.9.2"
downloads: 6
stars: 0
---

# ReasoningV-7B

> ReasoningV-7B - GipsyAI 在 ModelScope 开源的模型。If you find our work helpful, feel free to give us a cite 👇

GipsyAI/ReasoningV-7B 是 ModelScope 魔搭社区上的 7.6B 参数机器学习模型，可用 deploy_task text/emb、lmdeploy 0.9.1、lmdeploy_turbomind 0.9.1 部署。

- **Repository**: GipsyAI/ReasoningV-7B
- **Parameters**: 7.6B
- **Inference backends**: deploy_task text/emb, lmdeploy 0.9.1, lmdeploy_turbomind 0.9.1, sglang 0.5.2, vllm 0.9.2
- **Downloads**: 6
- **Stars**: 0
- **Last updated**: 2025-10-12

Source: https://www.modelscope.cn/models/GipsyAI/ReasoningV-7B

---

# Citation

If you find our work helpful, **feel free to give us a cite** 👇

> 📄 **Reference:**  
> [https://arxiv.org/abs/2504.14560](https://arxiv.org/abs/2504.14560)

```bibtex
@misc{reasoningv2025,
      title={ReasoningV: Efficient Verilog Code Generation with Adaptive Hybrid Reasoning Model}, 
      author={Haiyan Qin and Zhiwei Xie and Jingjing Li and Liangchen Li and Xiaotong Feng and Junzhan Liu and Wang Kang},
      year={2025},
      eprint={2504.14560},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2504.14560},
}
```