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license: mit
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base_model: AlicanKiraz0/QwQ-32B-Preview-SenecaLLMv1.2
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- gguf-my-repo
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# AlicanKiraz0/QwQ-32B-Preview-SenecaLLMv1.2-Q8_0-GGUF
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This model was converted to GGUF format from [`AlicanKiraz0/QwQ-32B-Preview-SenecaLLMv1.2`](https://huggingface.co/AlicanKiraz0/QwQ-32B-Preview-SenecaLLMv1.2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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---
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license: mit
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base_model: AlicanKiraz0/QwQ-32B-Preview-SenecaLLMv1.2
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pipeline_tag: text-classification
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tags:
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- gguf-my-repo
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- llama-cpp
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- qwen2.5
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- pentest
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- ethical-hacking
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- informationsecurity
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<img src="https://huggingface.co/AlicanKiraz0/SenecaLLM_x_Qwen2.5-7B-CyberSecurity-Q4_K_M-GGUF/resolve/main/SenecaLLMxqwen2.5-7B.webp" width="1000" />
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Curated and trained by Alican Kiraz
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[](https://tr.linkedin.com/in/alican-kiraz)
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Links:
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- Medium: https://alican-kiraz1.medium.com/
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- Linkedin: https://tr.linkedin.com/in/alican-kiraz
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- X: https://x.com/AlicanKiraz0
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- YouTube: https://youtube.com/@alicankiraz0
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SenecaLLM has been trained and fine-tuned for nearly one month—around 100 hours in total—using various systems such as 1x4090, 8x4090, and 3xH100, focusing on the following cybersecurity topics. Its goal is to think like a cybersecurity expert and assist with your questions. It has also been fine-tuned to counteract malicious use.
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**It does not pursue any profit.**
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Over time, it will specialize in the following areas:
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- Incident Response
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- Threat Hunting
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- Code Analysis
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- Exploit Development
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- Reverse Engineering
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- Malware Analysis
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"Those who shed light on others do not remain in darkness..."
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# AlicanKiraz0/QwQ-32B-Preview-SenecaLLMv1.2-Q8_0-GGUF
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This model was converted to GGUF format from [`AlicanKiraz0/QwQ-32B-Preview-SenecaLLMv1.2`](https://huggingface.co/AlicanKiraz0/QwQ-32B-Preview-SenecaLLMv1.2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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