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  • pdf文档 DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

    104K 116K 128K Context Length (#Tokens) 0 9 18 27 36 45 55 64 73 82 91 100 Document Depth Percent (%) Pressure Testing DeepSeek-V2 Base 128K Context via "Needle In A HayStack" 1 2 3 4 Lin, K. Zhu, Z. Ye, L. Chen, S. Zheng, L. Ceze, A. Krishnamurthy, T. Chen, and B. Kasikci. Atom: Low-bit quantization for efficient and accurate LLM serving. CoRR, abs/2310.19102, 2023. URL https://doi.org/10
    0 码力 | 52 页 | 1.23 MB | 1 年前
    3
  • pdf文档 Trends Artificial Intelligence

    Source: Epoch AI (4/25) AI Technology Compounding = Numbers Behind The Momentum Performance, 16-bit FLOP/s +150% / Year Enabled by 1.6x annual growth in chips per cluster and 1.6x annual growth platforms will push breadth, stitching together knowledge across functions; specialists will push depth, delivering AI that speaks the language of compliance, contracts, and customer intent. The question
    0 码力 | 340 页 | 12.14 MB | 5 月前
    3
  • pdf文档 清华大学 DeepSeek+DeepResearch 让科研像聊天一样简单

    stable cyclic performance, while providing high capacity and high voltage curves, has sparked in-depth research and discussion. As a promising candidate for anode materials, alloy-based anodes such as Among various options, alloy-based anodes, especially silicon (Si, 4200 mA h g-1), have sparked in-depth research and discussion. This is primarily due to their extremely high theoretical capacity, which
    0 码力 | 85 页 | 8.31 MB | 8 月前
    3
  • pdf文档 TVM@Alibaba AI Labs

    140 100 50 0 1 aTF Lite gbit aNCNN 8bit aQNNPACK 8bit aaMNN 8bit TVM Overflow-aware 四ACE Overflow-aware (Assembly) [和| Alibaba AL.Labs
    0 码力 | 12 页 | 1.94 MB | 6 月前
    3
  • pdf文档 Google 《Prompt Engineering v7》

    years between my partner and me and add those up. (20+(9-3)). Let’s help the model to think a little bit more like me. Prompt Engineering February 2025 31 Table 12 is an example of ‘zero-shot’ Chain of paths by branching out from different nodes in the tree. There’s a great notebook, which goes into a bit more detail showing The Tree of Thought (ToT) which is based on the paper ‘Large Language Model Guided Please refer to the notebook14 hosted in the GoogleCloudPlatform Github repository, which goes into a bit more detail showing the actual LLM inputs and outputs with a more elaborate example. Prompt Engineering
    0 码力 | 68 页 | 6.50 MB | 7 月前
    3
  • pdf文档 亿联TVM部署

    step1 on Windows to generate the .dll for deployment 3. For application on 32bits, no support of 32bit tensorflow , a workround from FrozenGene a. python/tvm/contrib/ndk.py options = options if options
    0 码力 | 6 页 | 1.96 MB | 6 月前
    3
  • pdf文档 Deepseek R1 本地部署完全手册

    - 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: 24GB - GPU: RTX 3090(24GB
    0 码力 | 7 页 | 932.77 KB | 8 月前
    3
  • pdf文档 TVM Meetup: Quantization

    represented with a scale and a zero point http://on-demand.gputechconf.com/gtc/2017/presentation/s7310-8-bit-inference-with-tensorrt.pdf 𝑟𝑒𝑎𝑙_𝑣𝑎𝑙𝑢𝑒 = 𝑠𝑐𝑎𝑙𝑒 ∗ (𝑞𝑢𝑎𝑛𝑡𝑖𝑧𝑒𝑑_𝑣𝑎𝑙𝑢𝑒 − �
    0 码力 | 19 页 | 489.50 KB | 6 月前
    3
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