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Model: dennny123/cybersec-qwen2.5-coder-7b
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: unsloth/Qwen2.5-Coder-7B-Instruct
+tags:
+- cybersecurity
+- security
+- cve
+- pentesting
+- fine-tuned
+- qwen2
+- unsloth
+pipeline_tag: text-generation
+---
+
+# Cybersecurity Fine-tuned Qwen2.5-Coder-7B
+
+This model was fine-tuned from `unsloth/Qwen2.5-Coder-7B-Instruct` on cybersecurity datasets using Unsloth + LoRA.
+
+## Training Details
+
+- **Base Model**: unsloth/Qwen2.5-Coder-7B-Instruct
+- **Parameters**: 7B
+- **Method**: LoRA fine-tuning
+- **LoRA Rank**: 16
+- **LoRA Alpha**: 32
+- **Training Examples**: 70,000
+- **Final Loss**: 0.7485
+- **Training Duration**: 31 minutes
+- **Hardware**: NVIDIA B200
+
+## Datasets Used
+
+| Dataset | Examples |
+|---------|----------|
+| omurkuru/cve-security-data | 20,000 |
+| Trendyol/Cybersecurity-Instruction | 10,000 |
+| ethanolivertroy/nist-cybersecurity | 10,000 |
+| Nitral-AI/Cybersecurity-ShareGPT | 10,000 |
+| Vanessasml/cybersecurity_32k | 10,000 |
+| jason-oneal/pentest-agent-dataset | 10,000 |
+| **Total** | **70,000** |
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained(
+    "dennny123/cybersec-qwen2.5-coder-7b",
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained("dennny123/cybersec-qwen2.5-coder-7b")
+
+messages = [
+    {"role": "system", "content": "You are a cybersecurity expert assistant."},
+    {"role": "user", "content": "Explain CVE-2024-1234 and its impact"}
+]
+
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=512)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Capabilities
+
+- CVE vulnerability analysis
+- Security log analysis  
+- Penetration testing guidance
+- NIST compliance knowledge
+- Threat detection patterns
+- Incident response
+
+## License
+
+Apache 2.0