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苹果公司:2025 Apple Intelligence基础语言模型技术报告(英文版)(27页).pdf

上传人: 1****1 编号:899131 2025-09-03 27页 976.91KB

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1、Apple Intelligence FoundationLanguage ModelsTech Report 2025AppleWe introduce two multilingual,multimodal foundation language models that powerApple Intelligence features across Apple devices and services:(i)a3B-parameteron-device model optimized for Apple silicon through architectural innovations s

2、uchas KV-cache sharing and 2-bit quantization-aware training;and(ii)a scalable servermodel built on a novel Parallel-Track Mixture-of-Experts(PT-MoE)transformer thatcombines track parallelism,mixture-of-experts sparse computation,and interleavedgloballocal attention to deliver high quality with comp

3、etitive cost on Apples PrivateCloud Compute platform.Both models are trained on large-scale multilingual andmultimodal datasets sourced via responsible web crawling,licensed corpora,andhigh-quality synthetic data,then further refined with supervised fine-tuning and rein-forcement learning on a new a

4、synchronous platform.The resulting models supportseveral additional languages while understanding images and executing tool calls.Inpublic benchmarks and human evaluations,both the server model and the on-devicemodel match or surpass comparably sized open baselines.A new Swift-centric Foundation Mod

5、els framework exposes guided generation,constrained tool calling,and LoRA adapter fine-tuning,allowing developers to inte-grate these capabilities with a few lines of code.The latest advancements in AppleIntelligence models are grounded in our Responsible AI approach with safeguardslike content filt

6、ering and locale-specific evaluation,as well as our commitment toprotecting our users privacy with innovations like Private Cloud Compute.1IntroductionApple Intelligence integrates powerful generative AI right into the apps and experiencesusers turn to everyday,all while protecting their privacy.At

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根据《Apple Intelligence FoundationLanguage ModelsTech Report 2025》的内容,以下是全文关键点的概括: 1. **模型介绍**:Apple推出了两款多语言、多模态的基础语言模型,用于增强Apple设备和服务中的Apple Intelligence功能。 2. **模型参数**:设备端模型约3B参数,服务器端模型基于PT-MoE架构。 3. **训练数据**:使用大规模多语言和多模态数据集,包括通过负责任的网络抓取、授权语料库和高质量合成数据。 4. **模型能力**:支持多种语言,理解图像,执行工具调用。 5. **模型优化**:设备端模型采用KV缓存共享和2位量化感知训练,服务器端模型采用PT-MoE架构和交错全局-局部注意力机制。 6. **开发框架**:Swift-centric Foundation Models框架,提供引导生成、约束工具调用和LoRA适配器微调功能。 7. **隐私保护**:采用内容过滤、地域特定评估和私有云计算等创新技术保护用户隐私。
揭秘多语言能力" 图像理解与工具调用" 轻松集成AI生成功能"
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