README.md

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title: TorchSight emoji: 🔥 colorFrom: orange colorTo: red sdk: static pinned: false

TorchSight

On-premises cybersecurity scanner powered by fine-tuned LLMs. Detects credentials, PII, malicious payloads, and sensitive data in text, images, and PDFs — without sending data to the cloud.

Models

• beam-q4_K_M — 95.1% accuracy, 17GB (recommended)
• beam-q8_0 — 92.7% accuracy, 28GB
• beam-f16 — 93.0% accuracy, 53GB

Datasets

• cybersecurity-classification-benchmark — 1052-sample eval benchmark
• beam-training-data — 74K SFT training samples

Highlights

• Beats Claude Opus 4 (79.9%), Gemini 2.5 Pro (75.4%) on domain classification
• LoRA fine-tune of Qwen 3.5 27B, runs locally via Ollama
• Apache 2.0 licensed

GitHub