metadata
license: other
language:
- en
tags:
- security
- cybersecurity
- vulnerability
- threat-intelligence
- anti-hallucination
- custom-architecture
- ordinal
library_name: transformers
pipeline_tag: text-generation
model-index:
- name: ordinal-5b
results:
- task:
type: text-generation
dataset:
name: Ordinal Security Dataset
type: custom
metrics:
- type: accuracy
value: 0.796
name: SecurityBench Score
- type: accuracy
value: 0.92
name: Anti-Hallucination Score
🛡️ Ordinal LLM — ordinal-5b
5.0B Security-Specialized Language Model with Anti-Hallucination Architecture
⚠️ This is the model architecture and configuration. Trained weights will be uploaded separately after training.
Architecture
| Parameter | Value |
|---|---|
| Parameters | ~5.0B |
| Hidden Size | 3584 |
| Layers | 36 |
| Attention Heads | 28 (GQA: 4 KV heads) |
| Head Dim | 128 |
| Intermediate | 9216 |
| Vocab Size | 50304 |
| Max Context | 8192 |
| Dtype | bfloat16 |
Anti-Hallucination Features
- Confidence Head: Per-token reliability score (threshold: 0.7)
- Retrieval-Augmented Attention: 4 retrieval heads, dim=256
- Fact Verification Layers: At layers [12, 24, 35]
- Source Grounding Embeddings: 16 source types
Usage
from transformers import AutoModelForCausalLM, AutoConfig
# Load config
config = AutoConfig.from_pretrained("Haruster/ordinal-5b", trust_remote_code=True)
# Load model (after weights are uploaded)
model = AutoModelForCausalLM.from_pretrained("Haruster/ordinal-5b", trust_remote_code=True)
Chat Template
<|system|>
You are Ordinal, a cybersecurity AI assistant.<|end_turn|>
<|user|>
What is CVE-2021-44228?<|end_turn|>
<|assistant|>
Training Data
17,000+ instruction/response pairs from verified public databases:
- NVD CVEs (CRITICAL/HIGH/MEDIUM/LOW)
- MITRE ATT&CK (techniques, groups, software)
- CAPEC attack patterns
- CISA KEV (actively exploited)
- GitHub Security Advisories
- 500+ anti-hallucination training examples
Recommended Hardware
| Quantization | VRAM Required |
|---|---|
| FP16 | ~10 GB |
| INT8 | ~5 GB |
| INT4 | ~2 GB |
Citation
@software{ordinal_llm_2026,
title={Ordinal LLM: Security-Specialized Language Model},
author={KaztoRay},
year={2026},
url={https://github.com/Haruster/Ordinal}
}