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Source channel @githubredteam · Post #82601 · 5月3日

🚨 GitHub 监控消息提醒 🚨发现关键词:#漏洞#利用#分析 📦项目名称:cve-llm-kg 👤项目作者:nantangqiuweiwan 🛠开发语言: Python ⭐Star数量: 1 | 🍴Fork数量: 0 📅更新时间: 2026-05-03 09:58:37 📝项目描述: 基于 LLM 的 CVE 漏洞知识图谱构建与分析:针对网络协议相关的 CVE 漏洞,设计 Prompt,利用大语言模型作为“智能解析器”,从非结构化的 CVE 描述中自动抽取关键实体和关系。将抽取出的实体和关系导入图数据库,构建一个可视化的物联网漏洞知识图谱。 🔗点击访问项目地址

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@githubtrending · Post #15600 · 2026/04/04 11:30

#python#apple_silicon#florence2#idefics#llava#llm#local_ai#mlx#molmo#paligemma#pixtral#vision_framework#vision_language_model#vision_transformer MLX-VLM lets you run, chat with, and fine-tune Vision Language Models (VLMs) plus audio/video models on your Mac using MLX—install easily with `pip install -U mlx-vlm`. Use CLI for quick text/image/audio generation (e.g., `mlx_vlm.generate --model ... --image photo.jpg`), Gradio UI for chats, Python scripts, or a FastAPI server with OpenAI-compatible endpoints supporting multi-images/videos. Features like TurboQuant cut KV cache memory by 76%, and LoRA/QLoRA fine-tuning works on consumer hardware. You benefit by experimenting with powerful multimodal AI locally—fast, memory-efficient, no cloud costs, perfect for Mac users tweaking models affordably. https://github.com/Blaizzy/mlx-vlm