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Source channel @lambdaexpression · Post #206 · 4月20日

前段时间一直被MajdataPlay的外键输入问题困扰:有玩家反映majplay会无征兆地出现拖判和吃音,但是内屏一切正常 因为我是第一次接触游戏开发,IO这方面也完全没经验 一开始我和bb本怀疑是线程调度的问题,即:IO线程时间片被其他线程挤占了,导致IO线程无法及时处理HID设备回报。为了验证这个猜想,我们尝试提高了IO线程的优先级,照旧 接下来我怀疑是我那套框架有问题:majplay是根据上一帧与这一帧的按键状态判断按键是不是"click"。为此我重写了这部分的实现,改进了IO线程与主线程之间的交互,问题照旧....... 到这里我已经怀疑这不是majplay的锅:IO线程没有任何异常,IO线程与主线程的交互没有问题,Note判定逻辑也没有问题,那就是设备确实没有回报给majplay或者设备发过来的回报中按键确实没有按下,但是大佬说hdd没有这种问题.....(人已经快崩溃了,这完全看不透也摸不着,因为我用单片机模拟玩家打高速纵连是完全没有问题的,我在家里用手台测试也没有问题) 到最后,bb本灵光一闪,说有没有可能是led刷新率过高,把按键控制板干爆炸了?我们让大佬把led刷新间隔从16ms改成100ms,吃音问题瞬间没有了,无语了 。。。。。。。。。。。。。。。。。。。。 adx是一个控制板同时管理按键和led,为什么我没有遇到吃音问题呢,因为我的手台不是adx的... #dev

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

👥 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 · 2026/04/09 12:14

🚀 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 · 2025/07/03 13:30

#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