关键词 "Curated collections" 的搜索结果, 共 24 条, 只显示前 480 条
A curated compilation of Model Context Protocol (MCP) servers assembled by Waqas from various sources including ChatHub and mcpservers.org
A curated, opinionated list of high-quality remote Model Context Protocol (MCP) servers.
This server enables AI models & Agents to interact with and search data from multiple curated sources through a unified MCP (model context protocol) server..
MCP server for connecting to you typesense collections and retrieve data using your favorite MCP client (Claude/ Cursor)
A curated list of Model Context Protocol (MCP) servers and tools. Discover and explore various MCP implementations that enable AI models to connect with external data sources and tools.
A community-curated collection of Open-Source MCP servers.
A curated list of awesome Model Context Protocol (MCP) servers.
MCPilled.com is a collection of curated news about MCP servers, clients, protocol updates and everything else MCP
Awesome MCP Servers - A curated list of Model Context Protocol servers
🔗 A curated list of Blockchain & Crypto Model Context Protocol (MCP) servers. Enabling AI Agents to interact with the Blockchain, Web3, DeFi, on-chain data, on-chain actions, etc. 🚀
A curated list of the most popular Model Context Protocol (MCP) servers based on usage data from Smithery.ai
An intelligent MCP server that serves as a guardian of development knowledge, providing Cline assistants with curated access to latest documentation and best practices across the software development
A curated list of awesome-mcp-servers (Model Context Protocol server)
A curated list of Model Context Protocol (MCP) servers optimized for Claude AI assistants.
A curated list of Hosted & Managed Model Context Protocol (MCP) Servers accessible via a simple URL endpoint.
The Milvus MCP server enables AI applications to interact with Milvus vector databases using natural language commands. It allows AI models to perform vector searches, manage collections, and retrieve
VACE(Video Creation and Editing)是阿里巴巴通义实验室推出的一站式视频生成与编辑框架。基于整合多种视频任务(如参考视频生成、视频到视频编辑、遮罩编辑等)到一个统一模型中,实现高效的内容创作和编辑功能。VACE的核心在于Video Condition Unit(VCU),将文本、图像、视频和遮罩等多种模态输入整合为统一的条件单元,支持多种任务的灵活组合。开源的 Wan2
WebThinker是中国人民大学、北京智源人工智能研究院和华为泊松实验室等机构提出的深度研究智能体。WebThinker赋能大型推理模型(LRMs)在推理过程中自主进行网络搜索、网页导航和报告撰写。WebThinker基于深度网页探索器和自主思考、搜索、写作策略,让LRMs能动态获取信息,实时生成高质量研究报告。WebThinker基于强化学习的训练策略进一步优化工具使用效率。WebThinke
NVILA是NVIDIA推出的系列视觉语言模型,能平衡效率和准确性。模型用“先扩展后压缩”策略,有效处理高分辨率图像和长视频。NVILA在训练和微调阶段进行系统优化,减少资源消耗,在多项图像和视频基准测试中达到或超越当前领先模型的准确性,包括Qwen2VL、InternVL和Pixtral在内的多种顶尖开源模型,及GPT-4o和Gemini等专有模型。NVILA引入时间定位、机器人导航和医学成像等
视觉语言模型(VLM),基于像素空间推理增强模型对视觉信息的理解和推理能力。模型能直接在视觉输入上进行操作,如放大图像区域或选择视频帧,更细致地捕捉视觉细节。Pixel Reasoner用两阶段训练方法,基于指令调优让模型熟悉视觉操作,用好奇心驱动的强化学习激励模型探索像素空间推理。Pixel Reasoner在多个视觉推理基准测试中取得优异的成绩,显著提升视觉密集型任务的性能。 Pixel R
VRAG-RL是阿里巴巴通义大模型团队推出的视觉感知驱动的多模态RAG推理框架,专注于提升视觉语言模型(VLMs)在处理视觉丰富信息时的检索、推理和理解能力。基于定义视觉感知动作空间,让模型能从粗粒度到细粒度逐步获取信息,更有效地激活模型的推理能力。VRAG-RL引入综合奖励机制,结合检索效率和基于模型的结果奖励,优化模型的检索和生成能力。在多个基准测试中,VRAG-RL显著优于现有方法,展现在视
MiniMax-M1是MiniMax团队最新推出的开源推理模型,基于混合专家架构(MoE)与闪电注意力机制(lightning attention)相结合,总参数量达 4560 亿,每个token激活 459 亿参数。模型超过国内的闭源模型,接近海外的最领先模型,具有业内最高的性价比。MiniMax-M1原生支持 100 万token的上下文长度,提供40 和80K两种推理预算版本,适合处理长输入
Lingshu是阿里巴巴达摩院推出的专注于医学领域的多模态大型语言模型。模型支持超过12种医学成像模态,包括X光、CT扫描、MRI等,在多模态问答、文本问答及医学报告生成等任务上展现出卓越的性能。Lingshu基于多阶段训练,逐步嵌入医学专业知识,显著提升在医学领域的推理和问题解决能力。推出7B、32B两个参数版本,其中32B版本在多个医学多模态问答任务中超越GPT-4.1等专有模型。Lingsh
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