关键词 "Semantic Testing" 的搜索结果, 共 16 条, 只显示前 480 条
Model Context Protocol (MCP) server implementation for semantic vector search and memory management using TxtAI. This server provides a robust API for storing, retrieving, and managing text-based memo
A FastMCP server implementation for the Semantic Scholar API, providing comprehensive access to academic paper data, author information, and citation networks.
A testing ground for the MCP server terminator. Hasta la vista, bugs!
Python-based MCP toolset with Echo server for testing and Browser Automation server using browser-use and LangChain for AI-driven web interactions
Allow MCP server to operate browser for testing purposes
All-in-one security testing toolbox that brings together popular open source tools through a single MCP interface. Connected to an AI agent, it enables tasks like pentesting, bug bounty hunting, threa
NOT for educational purposes: An MCP server for professional penetration testers including nmap, go/dirbuster, nikto, JtR, wordlist building, and more.
Creating ai-web-automation project for implementing use of AI prompts and MCP server in automation testing
Knowledge management system that allows you to build a persistent semantic graph from conversations with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you
MCP server providing semantic memory and persistent storage capabilities for Claude using ChromaDB and sentence transformers.
I am Abinanda and I am Main Head of The project so I am Trying to make a Server like Hypixel in Mcpe With Private and Public+Paid Plugins
DreamFit是什么 DreamFit是字节跳动团队联合清华大学深圳国际研究生院、中山大学深圳校区推出的虚拟试衣框架,专门用在轻量级服装为中心的人类图像生成。框架能显著减少模型复杂度和训练成本,基于优化文本提示和特征融合,提高生成图像的质量和一致性。DreamFit能泛化到各种服装、风格和提示指令,生成高质量的人物图像。DreamFit支持与社区控制插件的无缝集成,降低使用门槛。 Dre
IFAdapter是一种新型的文本到图像生成模型,由腾讯和新加坡国立大学共同推出。提升生成含有多个实例的图像时的位置和特征准确性。传统模型在处理多实例图像时常常面临定位和特征准确性的挑战,IFAdapter通过引入两个关键组件外观标记(Appearance Tokens)和实例语义图(Instance Semantic Map)解决问题。外观标记用于捕获描述中的详细特征信息,实例语义图则将特征与特
ViLAMP(VIdeo-LAnguage Model with Mixed Precision)是蚂蚁集团和中国人民大学联合推出的视觉语言模型,专门用在高效处理长视频内容。基于混合精度策略,对视频中的关键帧保持高精度分析,显著降低计算成本提高处理效率。ViLAMP在多个视频理解基准测试中表现出色,在长视频理解任务中,展现出显著优势。ViLAMP能在单张A100 GPU上处理长达1万帧(约3小时)
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