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Source channel @olddriverGDstudy · Post #9 · Mar 17

#语录 凡哥语录 也许大家会觉得这里规矩多,甚至去年我还听说别人评价我们这是集中营,可是到头来,所谓“自由”的那些群如今一个个都凉了,只有我们健康持续的发展着,大队就是个平台,平台是属于大家的,我们就是帮你们维持好正常运营,别的真没多想,其实你们扪心自问,应该也有个中肯的评价吧 你这不够推拉,不能这么舔,你要说,我考虑一下,看你表现,下次给你准备点小惊喜 找女朋友炮友什么的,不能一味舔狗,要调动妹子的注意力和心情,不是说要pua人家,但是人pua不也是强调以我为主,讲究拉扯么,这个也一样的呀,当然啦,面对🐔还是给钱实在点,别整那些有的没的

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秀儿の科技软件|资源分享社🎀

@JianjiaoPD · Post #9506 · 10/04/2025, 10:01 AM

👥 KoboldCpp | 本地大模型一站式工具 刚开始在本地跑大模型,往往要折腾环境依赖、库文件兼容,体验极其繁琐。后来虽然有了 Ollama、llama.cpp 这类工具简化部署,但功能单一。KoboldCpp 在此基础上走得更远:既继承了 llama.cpp 的高效推理,又保持了 Ollama 式的简单易用,只需下载一个可执行文件,就能直接运行 它不仅支持 CPU/GPU 双模式,还额外集成了 图像生成、语音识别、文字转语音 等多模态 AI 功能,并且兼容 OpenAI、Ollama 等主流 API,能无缝接入现有服务。跨平台支持 Windows、macOS、Linux,真正做到了开箱即用,对想要体验多功能本地大模型的用户来说非常友好 😎小编有话说:装环境那套折磨人,这玩意儿就是“懒人直装版” 👩‍💻KoboldCpp 标签:#KoboldCpp#大模型#本地部署#llamacpp#Ollama#AI 🗓@xiuerSearch 搜索历史资源 ✈️频道 | 💬群聊 | 📱中文包

Crypto M - Crypto News

@CryptoM · Post #64634 · 04/09/2026, 12:14 PM

🚀 AI TRENDS | Tether Launches QVAC SDK for Cross-Platform AI Development Tether has introduced the QVAC SDK, a unified software development kit designed to enable developers to build, run, and fine-tune AI applications directly on any device. According to Foresight News, this SDK ensures consistency across different environments. Applications developed using the QVAC SDK can seamlessly operate on platforms such as iOS, Android, Windows, macOS, and Linux. The same codebase can function across all supported environments without the need for platform-specific branches, rewrites, or conditional logic. The QVAC SDK is built on QVAC Fabric, a branch of llama.cpp, offering broad compatibility with the llama.cpp model ecosystem for text generation, embedding, and multimodal workloads. #AI#SDK#CrossPlatform#MachineLearning#LlamaCpp#SoftwareDevelopment#Multimodal#QVAC

GitHub Trends

@githubtrending · Post #14907 · 07/03/2025, 01:30 PM

#python#agents#generative_ai_tools#llamacpp#llm#onnx#openvino#parsing#retrieval_augmented_generation#small_specialized_models llmware is a powerful, easy-to-use platform that helps you build AI applications using small, specialized language models designed for business tasks like question-answering, summarization, and data extraction. It supports private, secure deployment on your own machines without needing expensive GPUs, making it cost-effective and safe for enterprise use. You can organize and search your documents, run smart queries, and combine knowledge with AI to get accurate answers quickly. It also offers many ready-to-use models and examples, plus tools for building chatbots and agents that automate complex workflows. This helps you save time, improve accuracy, and securely leverage AI for your business needs[1][3][5]. https://github.com/llmware-ai/llmware