---
license: apache-2.0
base_model: deepseek-ai/DeepSeek-R1-0528-Qwen3-8B
tags:
- cybersecurity
- security
- deepseek
- fine-tuned
- merged
- text-generation
datasets:
- Trendyol/Trendyol-Cybersecurity-Instruction-Tuning-Dataset
- AlicanKiraz0/Cybersecurity-Dataset-Fenrir-v2.0
language:
- en
pipeline_tag: text-generation
library_name: transformers
inference: true
---

# DeepSeek-R1-Cybersecurity-8B-Merged

This is the **merged** version of [sainikhiljuluri/DeepSeek-R1-Cybersecurity-8B](https://huggingface.co/sainikhiljuluri/DeepSeek-R1-Cybersecurity-8B), 
where the LoRA adapter has been merged into the base model for easier deployment.

## Model Description

Fine-tuned **deepseek-ai/DeepSeek-R1-0528-Qwen3-8B** specialized for **cybersecurity** tasks.
This merged model can be loaded directly without needing PEFT.

## Training Details

| Parameter | Value |
|-----------|-------|
| Base Model | deepseek-ai/DeepSeek-R1-0528-Qwen3-8B |
| Training Samples | ~50,000 |
| Epochs | 2 |
| LoRA Rank | 16 |
| LoRA Alpha | 32 |
| Learning Rate | 2e-4 |

## Usage

### Direct Loading
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model = AutoModelForCausalLM.from_pretrained(
    "sainikhiljuluri/DeepSeek-R1-Cybersecurity-8B-Merged",
    torch_dtype=torch.bfloat16,
    device_map="auto",
    trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained(
    "sainikhiljuluri/DeepSeek-R1-Cybersecurity-8B-Merged",
    trust_remote_code=True
)

prompt = "Explain how to detect SQL injection attacks."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=256, temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

### Via Inference API
```python
import requests

API_URL = "https://api-inference.huggingface.co/models/sainikhiljuluri/DeepSeek-R1-Cybersecurity-8B-Merged"
headers = {"Authorization": "Bearer YOUR_HF_TOKEN"}

response = requests.post(API_URL, headers=headers, json={
    "inputs": "What are the indicators of a ransomware attack?",
    "parameters": {"max_new_tokens": 256, "temperature": 0.7}
})
print(response.json())
```

## Cybersecurity Capabilities

- 🔍 Threat analysis and classification
- 🚨 Security alert triage  
- 📋 Incident response guidance
- 🦠 Malware analysis
- 📊 MITRE ATT&CK mapping
- 🔐 Vulnerability assessment