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sainikhiljuluri2015/Foundation-Sec-Cybersecurity-8B-Merged

sourceHugging Faceapache-2.0updated 10mo agoView on Hugging Face

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Model Card

Foundation-Sec-Cybersecurity-8B-Merged

Fine-tuned fdtn-ai/Foundation-Sec-8B specialized for cybersecurity tasks. This is a merged model (LoRA weights merged into base) for easy deployment.

Model Description

This model was trained on ~50,000 cybersecurity instruction-response pairs from:

—Trendyol Cybersecurity Dataset (35K samples)
—Fenrir v2.0 Dataset (12K samples)
—Primus-Instruct (3x upsampled)

Training Details

Parameter	Value
Base Model	fdtn-ai/Foundation-Sec-8B
Training Samples	~50,000
Epochs	2
LoRA Rank	16
LoRA Alpha	32
Learning Rate	2e-4
Max Sequence Length	1024
Target Modules	7 (qproj, kproj, vproj, oproj, gateproj, upproj, down_proj)

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model = AutoModelForCausalLM.from_pretrained(
    "sainikhiljuluri2015/Foundation-Sec-Cybersecurity-8B-Merged",
    torch_dtype=torch.bfloat16,
    device_map="auto",
    trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained("sainikhiljuluri2015/Foundation-Sec-Cybersecurity-8B-Merged", trust_remote_code=True)

prompt = "What are the indicators of a ransomware attack?"
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))

API Usage

python

import requests

API_URL = "https://YOUR_ENDPOINT_URL/v1/chat/completions"

response = requests.post(API_URL, json={
    "model": "sainikhiljuluri2015/Foundation-Sec-Cybersecurity-8B-Merged",
    "messages": [{"role": "user", "content": "What is SQL injection?"}],
    "max_tokens": 300
})
print(response.json()["choices"][0]["message"]["content"])

Cybersecurity Capabilities

—🔍 Threat analysis and classification
—🚨 Security alert triage
—📋 Incident response guidance
—🦠 Malware analysis
—📊 MITRE ATT&CK mapping
—🔐 Vulnerability assessment
—💉 SQL injection detection
—🎣 Phishing analysis
—🔑 CVE knowledge
—🛡️ Security best practices