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--- |
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base_model: unsloth/qwen2.5-coder-7b-instruct-bnb-4bit |
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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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- code-review |
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- static-analysis |
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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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- CyberNative/Code_Vulnerability_Security_DPO |
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--- |
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# Uploaded model |
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- **Developed by:** doss1232 |
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- **License:** apache-2.0 |
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- **Finetuned from model :** unsloth/qwen2.5-coder-7b-instruct-bnb-4bit |
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This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. |
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
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# Model information |
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Offensive-Qwen2.5-Coder-7b is a fine-tuned Qwen-2.5-Coder-7b model and a part of Offensive-Engine, a collection of models fine-tuned for cybersecurity. |
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It is train using the methods in **Automating Code Review Activities by Large-Scale Pre-training** paper. |
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Which means, it is suitable for code review and static analysis tasks, while still maintain coding capability. |
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Additionally, the model is further fine-tuned to find vulnerability in code, making it great for pentester and security professionals to use. |
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# Further improvment |
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This model will be use for Auto-Pentest Framework. |
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## Offensive-GenAI Framwork |
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Auto-Pentest is Agent system, built with Langchain to automate pentesting and web testing. |
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It is designed to work in corporation's source code, where security and confidentiality are preserverd. |
