among open-source models. The model checkpoints are available at h t t p s : / / g i t h u b . c o m / d e e p s e e k - a i / D e e p S e e k - V 2 . 0 20 40 60 80 100 Activated Parameters (Billions) higher data quality. We first pretrain DeepSeek-V2 on the full pre-training corpus. Then, we collect 1.5M conversational sessions, which encompass various domains such as math, code, writing, reasoning, safety (DeepSeek-AI, 2024), we curate our instruction tuning datasets to include 1.5M instances, comprising 1.2M instances for helpfulness and 0.3M instances for safety. In comparison to the initial version, we improve

= Rising Priority In a historic first for the [USA FDA], FDA Commissioner Martin A. Makary, M.D., M.P.H., today announced an aggressive timeline to scale use of artificial intelligence (AI) internally 63EF 220EF Annual Inference Tokens 50B 1T 5T 58T 1,375T +30,000x Annual Token Revenue $240K $3M $24M $300M $7B DC Power 37MW 34MW 25MW 19MW 21MW +50,000x Token Per MW-Year 1.3B 2.9B 200B 3T 65T …Performance This is just the beginning… …We doubled our compute at an unprecedented rate, with a roadmap to 1M GPUs. Progress in AI is driven by compute and no one has come close to building at this magnitude

voice; for a law firm, it means properly formatted citations, every time. Faster outcomes Less manual editing or re-checking means your teams can focus on high-value tasks. 15 AI in the EnterpriseLesson

4GB - GPU: 集成显卡/现代CPU - 存储: 5GB - 内存: 8GB （M1/M2/M3） - 存储: 5GB 简单⽂本⽣成、基础代 码补全 7B - RAM: 8-10GB - GPU: GTX 1680（4-bit量 化） - 存储: 8GB - 内存: 16GB（M2 Pro/M3） - 存储: 8GB 中等复杂度问答、代码 调试 14B - RAM: RAM: 24GB - GPU: RTX 3090（24GB VRAM） - 存储: 20GB - 内存: 32GB（M3 Max） - 存储: 20GB 复杂推理、技术⽂档⽣ 成 32B+ 企业级部署（需多卡并联） 暂不⽀持 科研计算、⼤规模数据 处理 2. 算⼒需求分析 模型 参数规 模 计算精 度 最低显存需 求 最低算⼒需求 DeepSeek-R1 (671B) 671B MoE模型部署（Ollama+Unsloth） 1. 量化⽅案与模型选择 量化版本 ⽂件体 积 最低内存+显存需 求 适⽤场景 DeepSeek-R1-UD- IQ1_M 158 GB ≥200 GB 消费级硬件（如Mac Studio） DeepSeek-R1-Q4_K_M 404 GB ≥500 GB ⾼性能服务器/云GPU 下载地址： HuggingFace模型库 Unsloth AI官⽅说明 2. 硬件配置建议

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Background 和 CUDA C half a[16x8] wmma::fragmentm, nm k halfwmma::col_major> a[1] a=Afindex] wmma::load_matrix_sync(a, &A[index], stride) mm matrix_a matrix_c [idx0, idx1] In, m] index0 indexl K m :matrix a m k matrix_a k n :matrix_b n k

需要修正的 五个示例模板和参考文献： 原始文本 修正后文本 Boullis A, Fassotte B, Sarles L,LognayG, Heuskin S, Vanderplanck M.Bartram S, Haubruge E, Francis F,Verheggen F(2017 Elevated Carbon Dioxide Concentration Reduces Alarm Aphids. J Chem Ecol 43:164-171. Boullis A, Fassotte B, Sarles L, Lognay G, Heuskin S, Vanderplanck M.Bartram S, Haubruge E, Francis F.Verheggen FJ (2017) Elevated CarbonDioxide Concentration Reduces 做一个视觉图表 What’s the main takeaway from this dataset? 找出最主要的信息 Can you explain this dataset like I’m 5 years old? 像给五岁小朋友讲故事那样解释一 下这个数据集 Can you create a presentation based this dataset? 做一个整体展示 Can

Performance Alios TVM @ ARM CPU INT8 Performance Comparison @ rasp 3b+ AARCH64 aoo0 8.87 sm ao 7m am sm 3.83 om ao 2.08 2 1.61 1.601.46 1.001 generate vec tvm,const(0， vrmpy instruction when we meet 人 ， GEM M. const(0， ，Vec_b ore(9，vdot) ib.emit(ou: 。 ore(0，vdot + outs[6] .vtoad( [6]， urn ib.get 驱动万物智能 Lake GPU 60.39% 512,512,512 国OpenVINO 国TVM 68.89% 1024 1024, 1024 PART Five Misc AiOS 1驱动万物智能 M Nvidia GTX 1050 。， Integrate other inference engine (like TRT) 2 _ _

S v L C q Y 4 Y V 1 T 8 0 u m B k k m O x d k C i y K r j i 6 n p Y d O w t v B 4 G 0 G p y 8 U I q e T 9 M 6 Deepseek的能力图谱 直接面向用户或者支持开发者，提供智能对话、

else [ “-shared”, “-fPIC”, “-m32”] b. python tensorflow_blur.py to get the .log c. Use the .log, with target=“llvm –mcpu=i686 –mtriple=i686-linux-gnu” then TVM_NDK_CC=“clang –m32” python tf_blur.py�����