AutoAudit—— the LLM for Cyber Security 网络安全大语言模型
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Updated
Feb 28, 2025 - HTML
AutoAudit—— the LLM for Cyber Security 网络安全大语言模型
Fine-tune your own LLM on an AMD Radeon GPU — the easy, tested way. QLoRA via ROCm on Windows/WSL2 & Linux, a worked Gemma-4 example, a reusable live training dashboard, and a smoke test that proves the loss falls.
🌐 Run GGUF models directly in your web browser using JavaScript and WebAssembly for a seamless and flexible AI experience.
Claude Code Mastery 2026 – 176 Expert Tips & Cheatsheet from 17 Repositories
Hands-on local LLM fine-tuning course (SFT / LoRA / PEFT / DPO / QLoRA) with a browser studio that visualizes loss, tensors, and adapter diffs.
Technical architecture for an AI-native Operating System. Features a 3-tier agentic hierarchy (Macro, Meso, Micro), Rust-based kernel, distributed error recovery, and nightly QLoRA self-learning loops
Production LoRA/QLoRA fine-tuning platform for LLMs: Gemma-2, Llama-3.2, Mistral-7B with PEFT, 4-bit quantization, DPO alignment and automated evaluation on custom datasets
QLoRA fine-tuning of a 1.2B model to beat 1T+ baselines on 7x7 grid spatial-design tasks
Cybersecurity threat intelligence assistant — fine-tuned Llama-3.1-8B on 9,992 NVD CVE records with dual-source RAG grounding (live NVD API + threat actor KB). Zero hallucinations on benchmark. SSE streaming. Two UI themes.
MIN-0 is an alphanumeric constructed language (conlang) spoken by MIN-0, a sentient automaton from the planet RB-0. The language encodes grammatical information - tense, voice, aspect, negation, modality, number, and more directly into alphanumeric symbol sequences using a deterministic rule-based algorithm.
Run Llama models in your web browser using JavaScript and WebAssembly. Explore light and dark modes easily. 🌐🐱👤
Project-aware AI architect assistant for the full SDLC. Per-project RAG, domain-adaptive fine-tuning (QLoRA), automated PR review, and a model registry — all self-hosted with Ollama.
Can a small VLM tell you if you can park in SF?
CLI-based AI tool for fine-tuning LLMs using LoRA & QLoRA with an efficient, modular pipeline.
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