石家庄哪个公司做网站好,用服务器ip做网站域名,创建一个平台需要什么,湖南百度推广用 itrex 创新高效实现 LLM 的部署和微调 - 项目作业 目录 准备工作Task 1 完成在线环境的工具包安装#xff0c;包含 基础环境包、Extension for Transformers 包、加速计算包Task 2 利用 Intel Extension for Transformers 部署通义千问 Qwen-7B Chat#xff0c;并根据 pr…用 itrex 创新高效实现 LLM 的部署和微调 - 项目作业 目录 准备工作Task 1 完成在线环境的工具包安装包含 基础环境包、Extension for Transformers 包、加速计算包Task 2 利用 Intel Extension for Transformers 部署通义千问 Qwen-7B Chat并根据 prompt 工程指定模型输出完成模型的加载转换、部署。1. prompt 设计利用特定分隔符完成指定格式的输出2. 部署模型在 /temp 目录下完成 Qwen-7B Chat 的加载、部署3. 输出模型输入作业 prompt 得到模型输出 准备工作
注意本项目是在和鲸的虚拟环境上运行的和本地实际部署流程可能会有差异 项目的难点在于调整设置prompt,不过文档中配置安装会占据较大篇幅直接浏览代码块就好。
计算资源腾讯云南京CPU16核64G 使用镜像3.11.8数据科学镜像
项目原链接 参考项目
Task 1 完成在线环境的工具包安装包含 基础环境包、Extension for Transformers 包、加速计算包
# Your Answer环境安装代码
# 安装Itrex在CPU环境下使用所需的系统环境
!sudo apt-get update
!sudo apt-get install -y ffmpeg
!sudo apt-get install -y libgl1-mesa-glx libgl1-mesa-dev
!sudo apt-get install -y libsm6 libxext6Get:1 http://archive.ubuntu.com/ubuntu jammy InRelease [270 kB]
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The following additional packages will be installed:libegl-dev libegl-mesa0 libegl1 libgl-dev libgles-dev libgles1 libgles2libglvnd-core-dev libglvnd-dev libglx-dev libopengl-dev libopengl0libpthread-stubs0-dev libx11-dev libxau-dev libxcb1-dev libxdmcp-devx11proto-dev xorg-sgml-doctools xtrans-dev
Suggested packages:libx11-doc libxcb-doc
The following NEW packages will be installed:libegl-dev libegl-mesa0 libegl1 libgl-dev libgl1-mesa-dev libgl1-mesa-glxlibgles-dev libgles1 libgles2 libglvnd-core-dev libglvnd-dev libglx-devlibopengl-dev libopengl0 libpthread-stubs0-dev libx11-dev libxau-devlibxcb1-dev libxdmcp-dev x11proto-dev xorg-sgml-doctools xtrans-dev
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0 upgraded, 0 newly installed, 0 to remove and 41 not upgraded.# 安装所需的第三方库包含环境依赖包和可选用于加速计算的依赖包
!conda install -y pytorch2.3.0 torchvision0.18.0 torchaudio2.3.0 cpuonly -c pytorch
!pip install cmake -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install ninja -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install neural_speed -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install intel-extension-for-transformers -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install modelscope -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install transformers -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install pyOpenSSL --upgrade -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install sentencepiece --upgrade -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install xformers -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install accelerate -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install tiktoken -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install transformers_stream_generator -i https://mirrors.cloud.tencent.com/pypi/simpleChannels:- pytorch- conda-forgePlatform: linux-64Collecting package metadata (repodata.json): doneSolving environment: done WARNING: A newer version of conda exists. current version: 24.3.0latest version: 24.5.0Please update conda by running$ conda update -n base -c conda-forge conda ## Package Plan ##environment location: /opt/condaadded / updated specs:- cpuonly- pytorch2.3.0- torchaudio2.3.0- torchvision0.18.0The following packages will be downloaded:package | build---------------------------|-----------------ca-certificates-2024.7.4 | hbcca054_0 151 KB conda-forgecertifi-2024.7.4 | pyhd8ed1ab_0 156 KB conda-forgecpuonly-2.0 | 0 2 KB pytorchffmpeg-4.3 | hf484d3e_0 9.9 MB pytorchfilelock-3.15.4 | pyhd8ed1ab_0 17 KB conda-forgegnutls-3.6.13 | h85f3911_1 2.0 MB conda-forgelame-3.100 | h166bdaf_1003 496 KB conda-forgelibabseil-20240116.2 | cxx17_he02047a_1 1.2 MB conda-forgelibtorch-2.3.0 |cpu_generic_h970db74_1 47.7 MB conda-forgenettle-3.6 | he412f7d_0 6.5 MB conda-forgeopenh264-2.1.1 | h780b84a_0 1.5 MB conda-forgeopenssl-3.3.1 | h4bc722e_2 2.8 MB conda-forgepytorch-2.3.0 |cpu_generic_py311h8ca351a_1 31.5 MB conda-forgepytorch-mutex-1.0 | cpu 3 KB pytorchsleef-3.6.1 | h3400bea_1 975 KB conda-forgetorchaudio-2.3.0 | py311_cpu 5.1 MB pytorchtorchvision-0.18.0 | py311_cpu 7.0 MB pytorch------------------------------------------------------------Total: 116.9 MBThe following NEW packages will be INSTALLED:cpuonly pytorch/noarch::cpuonly-2.0-0 ffmpeg pytorch/linux-64::ffmpeg-4.3-hf484d3e_0 filelock conda-forge/noarch::filelock-3.15.4-pyhd8ed1ab_0 gnutls conda-forge/linux-64::gnutls-3.6.13-h85f3911_1 lame conda-forge/linux-64::lame-3.100-h166bdaf_1003 libtorch conda-forge/linux-64::libtorch-2.3.0-cpu_generic_h970db74_1 nettle conda-forge/linux-64::nettle-3.6-he412f7d_0 openh264 conda-forge/linux-64::openh264-2.1.1-h780b84a_0 pytorch conda-forge/linux-64::pytorch-2.3.0-cpu_generic_py311h8ca351a_1 pytorch-mutex pytorch/noarch::pytorch-mutex-1.0-cpu sleef conda-forge/linux-64::sleef-3.6.1-h3400bea_1 torchaudio pytorch/linux-64::torchaudio-2.3.0-py311_cpu torchvision pytorch/linux-64::torchvision-0.18.0-py311_cpu The following packages will be UPDATED:ca-certificates 2024.2.2-hbcca054_0 -- 2024.7.4-hbcca054_0 certifi 2024.2.2-pyhd8ed1ab_0 -- 2024.7.4-pyhd8ed1ab_0 libabseil 20240116.1-cxx17_h59595ed_2 -- 20240116.2-cxx17_he02047a_1 openssl 3.2.1-hd590300_1 -- 3.3.1-h4bc722e_2 Downloading and Extracting Packages:libtorch-2.3.0 | 47.7 MB | | 0% pytorch-2.3.0 | 31.5 MB | | 0% [Affmpeg-4.3 | 9.9 MB | | 0% [A[Atorchvision-0.18.0 | 7.0 MB | | 0% [A[A[A
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tokenizers, pycocotools, transformers, neural-compressor, intel-extension-for-transformersSuccessfully installed deprecated-1.2.14 huggingface-hub-0.24.1 intel-extension-for-transformers-1.4.2 neural-compressor-2.6 opencv-python-headless-4.10.0.84 prettytable-3.10.2 pycocotools-2.0.8 regex-2024.5.15 safetensors-0.4.3 schema-0.7.7 tokenizers-0.19.1 transformers-4.43.1 wrapt-1.16.0Looking in indexes: https://mirrors.cloud.tencent.com/pypi/simpleCollecting modelscopeDownloading https://mirrors.cloud.tencent.com/pypi/packages/38/37/9fe505ebc67ba5e0345a69d6e8b2ee8630523975b484d221691ef60182bd/modelscope-1.16.1-py3-none-any.whl (5.7 MB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m5.7/5.7 MB[0m [31m4.1 MB/s[0m eta [36m0:00:00[0m00:01[0m00:01[0m[?25hRequirement already satisfied: requests2.25 in /opt/conda/lib/python3.11/site-packages (from modelscope) (2.31.0)Requirement already satisfied: tqdm4.64.0 in /opt/conda/lib/python3.11/site-packages (from modelscope) (4.66.2)Requirement 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torch2.3.1-xformers) (2024.3.1)Collecting nvidia-cuda-nvrtc-cu1212.1.105 (from torch2.3.1-xformers)Downloading https://mirrors.cloud.tencent.com/pypi/packages/b6/9f/c64c03f49d6fbc56196664d05dba14e3a561038a81a638eeb47f4d4cfd48/nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m23.7/23.7 MB[0m [31m10.7 MB/s[0m eta [36m0:00:00[0m00:01[0m00:01[0m[?25hCollecting nvidia-cuda-runtime-cu1212.1.105 (from torch2.3.1-xformers)Downloading https://mirrors.cloud.tencent.com/pypi/packages/eb/d5/c68b1d2cdfcc59e72e8a5949a37ddb22ae6cade80cd4a57a84d4c8b55472/nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m823.6/823.6 kB[0m [31m2.1 MB/s[0m eta [36m0:00:00[0m00:01[0m00:01[0m[?25hCollecting nvidia-cuda-cupti-cu1212.1.105 (from torch2.3.1-xformers)Downloading 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https://mirrors.cloud.tencent.com/pypi/packages/75/bc/e0d0dbb85246a086ab14839979039647bce501d8c661a159b8b019d987b7/nvidia_nvjitlink_cu12-12.5.82-py3-none-manylinux2014_x86_64.whl (21.3 MB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m21.3/21.3 MB[0m [31m9.1 MB/s[0m eta [36m0:00:00[0m00:01[0mm00:01[0m[?25hRequirement already satisfied: MarkupSafe2.0 in /opt/conda/lib/python3.11/site-packages (from jinja2-torch2.3.1-xformers) (2.1.5)Requirement already satisfied: mpmath0.19 in /opt/conda/lib/python3.11/site-packages (from sympy-torch2.3.1-xformers) (1.3.0)Installing collected packages: triton, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, torch, xformersAttempting uninstall: torchFound existing installation: torch 2.3.0Uninstalling torch-2.3.0:Successfully uninstalled torch-2.3.0Successfully installed nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.82 nvidia-nvtx-cu12-12.1.105 torch-2.3.1 triton-2.3.1 xformers-0.0.27Looking in indexes: https://mirrors.cloud.tencent.com/pypi/simpleCollecting accelerateDownloading https://mirrors.cloud.tencent.com/pypi/packages/15/33/b6b4ad5efa8b9f4275d4ed17ff8a44c97276171341ba565fdffb0e3dc5e8/accelerate-0.33.0-py3-none-any.whl (315 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m315.1/315.1 kB[0m [31m4.1 MB/s[0m eta [36m0:00:00[0m00:01[0m00:01[0m[?25hRequirement already satisfied: numpy2.0.0,1.17 in /opt/conda/lib/python3.11/site-packages (from accelerate) (1.26.4)Requirement already satisfied: packaging20.0 in /opt/conda/lib/python3.11/site-packages (from accelerate) (24.0)Requirement already satisfied: psutil in /opt/conda/lib/python3.11/site-packages (from accelerate) (5.9.8)Requirement already satisfied: pyyaml in /opt/conda/lib/python3.11/site-packages (from accelerate) (6.0.1)Requirement already satisfied: torch1.10.0 in /opt/conda/lib/python3.11/site-packages (from accelerate) (2.3.1)Requirement already satisfied: huggingface-hub0.21.0 in /opt/conda/lib/python3.11/site-packages (from accelerate) (0.24.1)Requirement already satisfied: safetensors0.3.1 in /opt/conda/lib/python3.11/site-packages (from accelerate) (0.4.3)Requirement already satisfied: filelock in /opt/conda/lib/python3.11/site-packages (from huggingface-hub0.21.0-accelerate) (3.15.4)Requirement already satisfied: fsspec2023.5.0 in /opt/conda/lib/python3.11/site-packages (from huggingface-hub0.21.0-accelerate) (2024.3.1)Requirement already satisfied: requests in /opt/conda/lib/python3.11/site-packages (from huggingface-hub0.21.0-accelerate) (2.31.0)Requirement already satisfied: tqdm4.42.1 in /opt/conda/lib/python3.11/site-packages (from huggingface-hub0.21.0-accelerate) (4.66.2)Requirement already satisfied: typing-extensions3.7.4.3 in /opt/conda/lib/python3.11/site-packages (from huggingface-hub0.21.0-accelerate) (4.10.0)Requirement already satisfied: sympy in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (1.12)Requirement already satisfied: networkx in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (3.2.1)Requirement already satisfied: jinja2 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (3.1.3)Requirement already satisfied: nvidia-cuda-nvrtc-cu1212.1.105 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (12.1.105)Requirement already satisfied: nvidia-cuda-runtime-cu1212.1.105 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (12.1.105)Requirement already satisfied: nvidia-cuda-cupti-cu1212.1.105 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (12.1.105)Requirement already satisfied: nvidia-cudnn-cu128.9.2.26 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (8.9.2.26)Requirement already satisfied: nvidia-cublas-cu1212.1.3.1 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (12.1.3.1)Requirement already satisfied: nvidia-cufft-cu1211.0.2.54 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (11.0.2.54)Requirement already satisfied: nvidia-curand-cu1210.3.2.106 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (10.3.2.106)Requirement already satisfied: nvidia-cusolver-cu1211.4.5.107 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (11.4.5.107)Requirement already satisfied: nvidia-cusparse-cu1212.1.0.106 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (12.1.0.106)Requirement already satisfied: nvidia-nccl-cu122.20.5 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (2.20.5)Requirement already satisfied: nvidia-nvtx-cu1212.1.105 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (12.1.105)Requirement already satisfied: triton2.3.1 in /opt/conda/lib/python3.11/site-packages (from torch1.10.0-accelerate) (2.3.1)Requirement already satisfied: nvidia-nvjitlink-cu12 in /opt/conda/lib/python3.11/site-packages (from nvidia-cusolver-cu1211.4.5.107-torch1.10.0-accelerate) (12.5.82)Requirement already satisfied: MarkupSafe2.0 in /opt/conda/lib/python3.11/site-packages (from jinja2-torch1.10.0-accelerate) (2.1.5)Requirement already satisfied: charset-normalizer4,2 in /opt/conda/lib/python3.11/site-packages (from requests-huggingface-hub0.21.0-accelerate) (3.3.2)Requirement already satisfied: idna4,2.5 in /opt/conda/lib/python3.11/site-packages (from requests-huggingface-hub0.21.0-accelerate) (3.6)Requirement already satisfied: urllib33,1.21.1 in /opt/conda/lib/python3.11/site-packages (from requests-huggingface-hub0.21.0-accelerate) (2.2.1)Requirement already satisfied: certifi2017.4.17 in /opt/conda/lib/python3.11/site-packages (from requests-huggingface-hub0.21.0-accelerate) (2024.7.4)Requirement already satisfied: mpmath0.19 in /opt/conda/lib/python3.11/site-packages (from sympy-torch1.10.0-accelerate) (1.3.0)Installing collected packages: accelerateSuccessfully installed accelerate-0.33.0Looking in indexes: https://mirrors.cloud.tencent.com/pypi/simpleCollecting tiktokenDownloading https://mirrors.cloud.tencent.com/pypi/packages/61/b4/b80d1fe33015e782074e96bbbf4108ccd283b8deea86fb43c15d18b7c351/tiktoken-0.7.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m1.1/1.1 MB[0m [31m7.7 MB/s[0m eta [36m0:00:00[0m00:01[0m00:01[0m[?25hRequirement already satisfied: regex2022.1.18 in /opt/conda/lib/python3.11/site-packages (from tiktoken) (2024.5.15)Requirement already satisfied: requests2.26.0 in /opt/conda/lib/python3.11/site-packages (from tiktoken) (2.31.0)Requirement already satisfied: charset-normalizer4,2 in /opt/conda/lib/python3.11/site-packages (from requests2.26.0-tiktoken) (3.3.2)Requirement already satisfied: idna4,2.5 in /opt/conda/lib/python3.11/site-packages (from requests2.26.0-tiktoken) (3.6)Requirement already satisfied: urllib33,1.21.1 in /opt/conda/lib/python3.11/site-packages (from requests2.26.0-tiktoken) (2.2.1)Requirement already satisfied: certifi2017.4.17 in /opt/conda/lib/python3.11/site-packages (from requests2.26.0-tiktoken) (2024.7.4)Installing collected packages: tiktokenSuccessfully installed tiktoken-0.7.0Looking in indexes: https://mirrors.cloud.tencent.com/pypi/simpleCollecting transformers_stream_generatorDownloading https://mirrors.cloud.tencent.com/pypi/packages/42/c2/65f13aec253100e1916e9bd7965fe17bde796ebabeb1265f45191ab4ddc0/transformers-stream-generator-0.0.5.tar.gz (13 kB)Preparing metadata (setup.py) ... [?25ldone[?25hRequirement already satisfied: transformers4.26.1 in /opt/conda/lib/python3.11/site-packages (from transformers_stream_generator) (4.43.1)Requirement already satisfied: filelock in /opt/conda/lib/python3.11/site-packages (from transformers4.26.1-transformers_stream_generator) (3.15.4)Requirement already satisfied: huggingface-hub1.0,0.23.2 in /opt/conda/lib/python3.11/site-packages (from transformers4.26.1-transformers_stream_generator) (0.24.1)Requirement already satisfied: numpy1.17 in /opt/conda/lib/python3.11/site-packages (from transformers4.26.1-transformers_stream_generator) (1.26.4)Requirement already satisfied: packaging20.0 in /opt/conda/lib/python3.11/site-packages (from transformers4.26.1-transformers_stream_generator) (24.0)Requirement already satisfied: pyyaml5.1 in /opt/conda/lib/python3.11/site-packages (from transformers4.26.1-transformers_stream_generator) (6.0.1)Requirement already satisfied: regex!2019.12.17 in /opt/conda/lib/python3.11/site-packages (from transformers4.26.1-transformers_stream_generator) (2024.5.15)Requirement already satisfied: requests in /opt/conda/lib/python3.11/site-packages (from transformers4.26.1-transformers_stream_generator) (2.31.0)Requirement already satisfied: tokenizers0.20,0.19 in /opt/conda/lib/python3.11/site-packages (from transformers4.26.1-transformers_stream_generator) (0.19.1)Requirement already satisfied: safetensors0.4.1 in /opt/conda/lib/python3.11/site-packages (from transformers4.26.1-transformers_stream_generator) (0.4.3)Requirement already satisfied: tqdm4.27 in /opt/conda/lib/python3.11/site-packages (from transformers4.26.1-transformers_stream_generator) (4.66.2)Requirement already satisfied: fsspec2023.5.0 in /opt/conda/lib/python3.11/site-packages (from huggingface-hub1.0,0.23.2-transformers4.26.1-transformers_stream_generator) (2024.3.1)Requirement already satisfied: typing-extensions3.7.4.3 in /opt/conda/lib/python3.11/site-packages (from huggingface-hub1.0,0.23.2-transformers4.26.1-transformers_stream_generator) (4.10.0)Requirement already satisfied: charset-normalizer4,2 in /opt/conda/lib/python3.11/site-packages (from requests-transformers4.26.1-transformers_stream_generator) (3.3.2)Requirement already satisfied: idna4,2.5 in /opt/conda/lib/python3.11/site-packages (from requests-transformers4.26.1-transformers_stream_generator) (3.6)Requirement already satisfied: urllib33,1.21.1 in /opt/conda/lib/python3.11/site-packages (from requests-transformers4.26.1-transformers_stream_generator) (2.2.1)Requirement already satisfied: certifi2017.4.17 in /opt/conda/lib/python3.11/site-packages (from requests-transformers4.26.1-transformers_stream_generator) (2024.7.4)Building wheels for collected packages: transformers_stream_generatorBuilding wheel for transformers_stream_generator (setup.py) ... [?25ldone[?25h Created wheel for transformers_stream_generator: filenametransformers_stream_generator-0.0.5-py3-none-any.whl size12425 sha25685aa383732526ad8e749a82f5d4ce7076efa0ee456db4843096e1c118609740cStored in directory: /home/mw/.cache/pip/wheels/c0/9f/f6/f8573ca658852aa7cdde5a0e2717f767ac9b2dd19a7d2897b9Successfully built transformers_stream_generatorInstalling collected packages: transformers_stream_generatorSuccessfully installed transformers_stream_generator-0.0.5
# 在temp目录下进行模型在cpu上的转换存储
%cd ..
%cd temp/home/mw
/home/mw/temp!pip install datasets -i https://mirrors.cloud.tencent.com/pypi/simple
!pip install einops -i https://mirrors.cloud.tencent.com/pypi/simpleLooking in indexes: https://mirrors.cloud.tencent.com/pypi/simpleCollecting datasetsDownloading https://mirrors.cloud.tencent.com/pypi/packages/60/2d/963b266bb8f88492d5ab4232d74292af8beb5b6fdae97902df9e284d4c32/datasets-2.20.0-py3-none-any.whl (547 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m547.8/547.8 kB[0m [31m2.3 MB/s[0m eta [36m0:00:00[0ma [36m0:00:01[0m[?25hRequirement already satisfied: filelock in /opt/conda/lib/python3.11/site-packages (from datasets) (3.15.4)Requirement already satisfied: numpy1.17 in /opt/conda/lib/python3.11/site-packages (from datasets) (1.26.4)Requirement already satisfied: pyarrow15.0.0 in /opt/conda/lib/python3.11/site-packages (from datasets) (15.0.2)Requirement already satisfied: pyarrow-hotfix in /opt/conda/lib/python3.11/site-packages (from datasets) (0.6)Requirement already satisfied: dill0.3.9,0.3.0 in /opt/conda/lib/python3.11/site-packages (from datasets) (0.3.8)Requirement already satisfied: pandas in /opt/conda/lib/python3.11/site-packages (from datasets) (2.2.1)Collecting requests2.32.2 (from datasets)Downloading https://mirrors.cloud.tencent.com/pypi/packages/f9/9b/335f9764261e915ed497fcdeb11df5dfd6f7bf257d4a6a2a686d80da4d54/requests-2.32.3-py3-none-any.whl (64 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m64.9/64.9 kB[0m [31m4.0 MB/s[0m eta [36m0:00:00[0m[?25hCollecting tqdm4.66.3 (from datasets)Downloading https://mirrors.cloud.tencent.com/pypi/packages/18/eb/fdb7eb9e48b7b02554e1664afd3bd3f117f6b6d6c5881438a0b055554f9b/tqdm-4.66.4-py3-none-any.whl (78 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m78.3/78.3 kB[0m [31m5.3 MB/s[0m eta [36m0:00:00[0m[?25hCollecting xxhash (from datasets)Downloading https://mirrors.cloud.tencent.com/pypi/packages/eb/3a/25c4aecb61a49d4415fd71d4f66a8a5b558dd44a52d7054ea9aa59ccbac1/xxhash-3.4.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m194.8/194.8 kB[0m [31m7.1 MB/s[0m eta [36m0:00:00[0m[?25hCollecting multiprocess (from datasets)Downloading https://mirrors.cloud.tencent.com/pypi/packages/50/15/b56e50e8debaf439f44befec5b2af11db85f6e0f344c3113ae0be0593a91/multiprocess-0.70.16-py311-none-any.whl (143 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m143.5/143.5 kB[0m [31m944.8 kB/s[0m eta [36m0:00:00[0ma [36m0:00:01[0m[?25hRequirement already satisfied: fsspec2024.5.0,2023.1.0 in /opt/conda/lib/python3.11/site-packages (from fsspec[http]2024.5.0,2023.1.0-datasets) (2024.3.1)Collecting aiohttp (from datasets)Downloading https://mirrors.cloud.tencent.com/pypi/packages/24/99/e76e65ca811100b445d3c8af9764b27c5180ca11a15af694366424896647/aiohttp-3.9.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m1.3/1.3 MB[0m [31m8.9 MB/s[0m eta [36m0:00:00[0m00:01[0m00:01[0m[?25hRequirement already satisfied: huggingface-hub0.21.2 in /opt/conda/lib/python3.11/site-packages (from datasets) (0.24.1)Requirement already satisfied: packaging in /opt/conda/lib/python3.11/site-packages (from datasets) (24.0)Requirement already satisfied: pyyaml5.1 in /opt/conda/lib/python3.11/site-packages (from datasets) (6.0.1)Collecting aiosignal1.1.2 (from aiohttp-datasets)Downloading https://mirrors.cloud.tencent.com/pypi/packages/76/ac/a7305707cb852b7e16ff80eaf5692309bde30e2b1100a1fcacdc8f731d97/aiosignal-1.3.1-py3-none-any.whl (7.6 kB)Requirement already satisfied: attrs17.3.0 in /opt/conda/lib/python3.11/site-packages (from aiohttp-datasets) (23.2.0)Collecting frozenlist1.1.1 (from aiohttp-datasets)Downloading https://mirrors.cloud.tencent.com/pypi/packages/b3/c9/0bc5ee7e1f5cc7358ab67da0b7dfe60fbd05c254cea5c6108e7d1ae28c63/frozenlist-1.4.1-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (272 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m272.3/272.3 kB[0m [31m9.3 MB/s[0m eta [36m0:00:00[0m[?25hCollecting multidict7.0,4.5 (from aiohttp-datasets)Downloading https://mirrors.cloud.tencent.com/pypi/packages/52/ec/be54a3ad110f386d5bd7a9a42a4ff36b3cd723ebe597f41073a73ffa16b8/multidict-6.0.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (128 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m128.7/128.7 kB[0m [31m63.7 kB/s[0m eta [36m0:00:00[0ma [36m0:00:01[0m[?25hCollecting yarl2.0,1.0 (from aiohttp-datasets)Downloading https://mirrors.cloud.tencent.com/pypi/packages/9f/ea/94ad7d8299df89844e666e4aa8a0e9b88e02416cd6a7dd97969e9eae5212/yarl-1.9.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (328 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m328.1/328.1 kB[0m [31m6.5 MB/s[0m eta [36m0:00:00[0ma [36m0:00:01[0m[?25hRequirement already satisfied: typing-extensions3.7.4.3 in /opt/conda/lib/python3.11/site-packages (from huggingface-hub0.21.2-datasets) (4.10.0)Requirement already satisfied: charset-normalizer4,2 in /opt/conda/lib/python3.11/site-packages (from requests2.32.2-datasets) (3.3.2)Requirement already satisfied: idna4,2.5 in /opt/conda/lib/python3.11/site-packages (from requests2.32.2-datasets) (3.6)Requirement already satisfied: urllib33,1.21.1 in /opt/conda/lib/python3.11/site-packages (from requests2.32.2-datasets) (2.2.1)Requirement already satisfied: certifi2017.4.17 in /opt/conda/lib/python3.11/site-packages (from requests2.32.2-datasets) (2024.7.4)Requirement already satisfied: python-dateutil2.8.2 in /opt/conda/lib/python3.11/site-packages (from pandas-datasets) (2.9.0)Requirement already satisfied: pytz2020.1 in /opt/conda/lib/python3.11/site-packages (from pandas-datasets) (2024.1)Requirement already satisfied: tzdata2022.7 in /opt/conda/lib/python3.11/site-packages (from pandas-datasets) (2024.1)Requirement already satisfied: six1.5 in /opt/conda/lib/python3.11/site-packages (from python-dateutil2.8.2-pandas-datasets) (1.16.0)Installing collected packages: xxhash, tqdm, requests, multiprocess, multidict, frozenlist, yarl, aiosignal, aiohttp, datasetsAttempting uninstall: tqdmFound existing installation: tqdm 4.66.2Uninstalling tqdm-4.66.2:Successfully uninstalled tqdm-4.66.2Attempting uninstall: requestsFound existing installation: requests 2.31.0Uninstalling requests-2.31.0:Successfully uninstalled requests-2.31.0Successfully installed aiohttp-3.9.5 aiosignal-1.3.1 datasets-2.20.0 frozenlist-1.4.1 multidict-6.0.5 multiprocess-0.70.16 requests-2.32.3 tqdm-4.66.4 xxhash-3.4.1 yarl-1.9.4Looking in indexes: https://mirrors.cloud.tencent.com/pypi/simpleCollecting einopsDownloading https://mirrors.cloud.tencent.com/pypi/packages/44/5a/f0b9ad6c0a9017e62d4735daaeb11ba3b6c009d69a26141b258cd37b5588/einops-0.8.0-py3-none-any.whl (43 kB)[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m43.2/43.2 kB[0m [31m1.9 MB/s[0m eta [36m0:00:00[0m[?25hInstalling collected packages: einopsSuccessfully installed einops-0.8.0
Task 2 利用 Intel Extension for Transformers 部署通义千问 Qwen-7B Chat并根据 prompt 工程指定模型输出完成模型的加载转换、部署。
请按照以下作业流程依次完成。
1. prompt 设计利用特定分隔符完成指定格式的输出
任务要求
1.1 给定一个段落让模型用一句话总结给定段落如下
《骆驼祥子》 祥子来自农村是个破产的青年农民勤劳、纯朴、善良保留着农村哺育他、教养他的一切却再也不愿意回农村去了。从农村来到城市的祥子渴望以自己的诚实劳动买一辆属于自己的车。做个独立的劳动者是祥子的志愿、希望、甚至是宗教凭着勤劳和坚忍他用三年的时间省吃俭用终于实现了理想成为自食其力的上等车夫。但刚拉半年车就在兵荒马乱中被逃兵掳走祥子失去了洋车只牵回三匹骆驼。祥子没有灰心他依然倔强地从头开始更加克己地拉车攒钱。可是还没有等他再买上车所有的积蓄又被侦探敲诈、洗劫一空买车的梦想再次成泡影。 祥子又一次拉上自己的车是以与虎妞成就畸形的婚姻为代价的。可惜好景不长因虎妞死于难产他不得不卖掉人力车去料理丧事。至此他的人生理想彻底破灭了。再加上他心爱的女人小福子的自杀吹熄了他心中最后一朵希望的火花。连遭生活的打击祥子开始丧失了对于生活的任何企求和信心再也无法鼓起生活的勇气不再像从前一样以拉车为自豪他厌恶拉车厌恶劳作。 被生活捉弄的祥子开始游戏生活吃喝嫖赌。为了喝酒祥子到处骗钱堕落为“城市垃圾”。最后靠给人干红白喜事做杂工维持生计。祥子由一个“体面的、要强的、好梦想的、利己的、个人的、健壮的、伟大的”底层劳动者沦为一个“堕落的、自私的、不幸的、社会病胎里的产儿个人主义的末路鬼”
1.2 给出该段话的英文翻译
1.3 给出这段话中能反映情绪的关键词
1.4 将最终结果以 json 格式输出
# 导入 Intel Extension for Transformers 相关函数
from transformers import AutoTokenizer, TextStreamer
from intel_extension_for_transformers.transformers import AutoModelForCausalLM# Your AnswerPrompt设计
prompt 根据给定的文本内容完成以下任务
1. 段落翻译为英文注意词汇底层劳动者、末路鬼的翻译。
2. 给出段落的一句话总结。
3. 给出这段话的情绪关键词列表。文本内容《骆驼祥子》祥子来自农村是个破产的青年农民勤劳、纯朴、善良保留着农村哺育他、教养他的一切却再也不愿意回农村去了。从农村来到城市的祥子渴望以自己的诚实劳动买一辆属于自己的车。做个独立的劳动者是祥子的志愿、希望、甚至是宗教凭着勤劳和坚忍他用三年的时间省吃俭用终于实现了理想成为自食其力的上等车夫。但刚拉半年车就在兵荒马乱中被逃兵掳走祥子失去了洋车只牵回三匹骆驼。祥子没有灰心他依然倔强地从头开始更加克己地拉车攒钱。可是还没有等他再买上车所有的积蓄又被侦探敲诈、洗劫一空买车的梦想再次成泡影。祥子又一次拉上自己的车是以与虎妞成就畸形的婚姻为代价的。可惜好景不长因虎妞死于难产他不得不卖掉人力车去料理丧事。至此他的人生理想彻底破灭了。再加上他心爱的女人小福子的自杀吹熄了他心中最后一朵希望的火花。连遭生活的打击祥子开始丧失了对于生活的任何企求和信心再也无法鼓起生活的勇气不再像从前一样以拉车为自豪他厌恶拉车厌恶劳作。被生活捉弄的祥子开始游戏生活吃喝嫖赌。为了喝酒祥子到处骗钱堕落为“城市垃圾”。最后靠给人干红白喜事做杂工维持生计。祥子由一个“体面的、要强的、好梦想的、利己的、个人的、健壮的、伟大的”底层劳动者沦为一个“堕落的、自私的、不幸的、社会病胎里的产儿个人主义的末路鬼”。以json格式输出任务结果格式规范易于阅读和解析# # Your AnswerPrompt设计
# prompt
# 根据文本内容完成任务
# 分别完成英文翻译”、“一句话总结”、“情绪关键词”结果的输出格式为json。
# {英文翻译:,一句话总结:,情绪关键词:}
# 文本内容《骆驼祥子》
# 祥子来自农村是个破产的青年农民勤劳、纯朴、善良保留着农村哺育他、教养他的一切却再也不愿意回农村去了。从农村来到城市的祥子渴望以自己的诚实劳动买一辆属于自己的车。做个独立的劳动者是祥子的志愿、希望、甚至是宗教凭着勤劳和坚忍他用三年的时间省吃俭用终于实现了理想成为自食其力的上等车夫。但刚拉半年车就在兵荒马乱中被逃兵掳走祥子失去了洋车只牵回三匹骆驼。祥子没有灰心他依然倔强地从头开始更加克己地拉车攒钱。可是还没有等他再买上车所有的积蓄又被侦探敲诈、洗劫一空买车的梦想再次成泡影。
# 祥子又一次拉上自己的车是以与虎妞成就畸形的婚姻为代价的。可惜好景不长因虎妞死于难产他不得不卖掉人力车去料理丧事。至此他的人生理想彻底破灭了。再加上他心爱的女人小福子的自杀吹熄了他心中最后一朵希望的火花。连遭生活的打击祥子开始丧失了对于生活的任何企求和信心再也无法鼓起生活的勇气不再像从前一样以拉车为自豪他厌恶拉车厌恶劳作。
# 被生活捉弄的祥子开始游戏生活吃喝嫖赌。为了喝酒祥子到处骗钱堕落为“城市垃圾”。最后靠给人干红白喜事做杂工维持生计。祥子由一个“体面的、要强的、好梦想的、利己的、个人的、健壮的、伟大的”底层劳动者沦为一个“堕落的、自私的、不幸的、社会病胎里的产儿个人主义的末路鬼”
# # # Your AnswerPrompt设计
# prompt
# 根据文本内容完成任务
# 1. 给出该段话的英文翻译。
# 2. 给出文本的一句话总结。
# 3. 给出这段话能反映情绪的关键词。
# 结果以json的格式输出分别对应“文本翻译”、“一句话总结”、“情绪关键词”。
# 文本内容《骆驼祥子》
# 祥子来自农村是个破产的青年农民勤劳、纯朴、善良保留着农村哺育他、教养他的一切却再也不愿意回农村去了。从农村来到城市的祥子渴望以自己的诚实劳动买一辆属于自己的车。做个独立的劳动者是祥子的志愿、希望、甚至是宗教凭着勤劳和坚忍他用三年的时间省吃俭用终于实现了理想成为自食其力的上等车夫。但刚拉半年车就在兵荒马乱中被逃兵掳走祥子失去了洋车只牵回三匹骆驼。祥子没有灰心他依然倔强地从头开始更加克己地拉车攒钱。可是还没有等他再买上车所有的积蓄又被侦探敲诈、洗劫一空买车的梦想再次成泡影。
# 祥子又一次拉上自己的车是以与虎妞成就畸形的婚姻为代价的。可惜好景不长因虎妞死于难产他不得不卖掉人力车去料理丧事。至此他的人生理想彻底破灭了。再加上他心爱的女人小福子的自杀吹熄了他心中最后一朵希望的火花。连遭生活的打击祥子开始丧失了对于生活的任何企求和信心再也无法鼓起生活的勇气不再像从前一样以拉车为自豪他厌恶拉车厌恶劳作。
# 被生活捉弄的祥子开始游戏生活吃喝嫖赌。为了喝酒祥子到处骗钱堕落为“城市垃圾”。最后靠给人干红白喜事做杂工维持生计。祥子由一个“体面的、要强的、好梦想的、利己的、个人的、健壮的、伟大的”底层劳动者沦为一个“堕落的、自私的、不幸的、社会病胎里的产儿个人主义的末路鬼”
# # prompt 1给定一个段落让模型用一句话总结给定段落如下
# 《骆驼祥子》
# 祥子来自农村是个破产的青年农民勤劳、纯朴、善良保留着农村哺育他、教养他的一切却再也不愿意回农村去了。从农村来到城市的祥子渴望以自己的诚实劳动买一辆属于自己的车。做个独立的劳动者是祥子的志愿、希望、甚至是宗教凭着勤劳和坚忍他用三年的时间省吃俭用终于实现了理想成为自食其力的上等车夫。但刚拉半年车就在兵荒马乱中被逃兵掳走祥子失去了洋车只牵回三匹骆驼。祥子没有灰心他依然倔强地从头开始更加克己地拉车攒钱。可是还没有等他再买上车所有的积蓄又被侦探敲诈、洗劫一空买车的梦想再次成泡影。
# 祥子又一次拉上自己的车是以与虎妞成就畸形的婚姻为代价的。可惜好景不长因虎妞死于难产他不得不卖掉人力车去料理丧事。至此他的人生理想彻底破灭了。再加上他心爱的女人小福子的自杀吹熄了他心中最后一朵希望的火花。连遭生活的打击祥子开始丧失了对于生活的任何企求和信心再也无法鼓起生活的勇气不再像从前一样以拉车为自豪他厌恶拉车厌恶劳作。
# 被生活捉弄的祥子开始游戏生活吃喝嫖赌。为了喝酒祥子到处骗钱堕落为“城市垃圾”。最后靠给人干红白喜事做杂工维持生计。祥子由一个“体面的、要强的、好梦想的、利己的、个人的、健壮的、伟大的”底层劳动者沦为一个“堕落的、自私的、不幸的、社会病胎里的产儿个人主义的末路鬼”
# 2 给出该段话的英文翻译
# 3 给出这段话中能反映情绪的关键词
# 将最终结果以 json 格式输出2. 部署模型在 /temp 目录下完成 Qwen-7B Chat 的加载、部署
任务要求
2.1 通过在数据集中外挂 Qwen-7B Chat 或者通过魔搭下载 Qwen-7B Chat 的方式完成模型加载
2.2 通过 AutoTokenizer 完成 tokenizer 的加载
2.3 通过 Intel Extension for Transformers 的 AutoModelForCausalLM 工具快速完成模型部署
# Your Answer模型加载和部署
model_dir /home/mw/input/qwen7bchat7438
tokenizer AutoTokenizer.from_pretrained(model_dir, trust_remote_codeTrue)
inputs tokenizer(prompt, return_tensorspt).input_ids
streamer TextStreamer(tokenizer)
model AutoModelForCausalLM.from_pretrained(model_dir, load_in_4bitTrue, trust_remote_codeTrue)
# model AutoModelForCausalLM.from_pretrained(model_dir, trust_remote_codeTrue) # 尝试直接加载FP32模型2024-07-24 08:12:53 [INFO] cpu device is used.
2024-07-24 08:12:53 [INFO] Applying Weight Only Quantization.
2024-07-24 08:12:53 [INFO] Quantize model by Neural Speed with RTN Algorithm.runtime_outs/ne_qwen_q_nf4_bestla_cfp32_g32.bin existed, will use cache file. Otherwise please remove the file
3. 输出模型输入作业 prompt 得到模型输出
outputs model.generate(inputs, streamerstreamer, max_new_tokens550)
# outputsload_ne_hparams 0.hparams.n_vocab 151936
load_ne_hparams 1.hparams.n_embd 4096
load_ne_hparams 2.hparams.n_mult 22016
load_ne_hparams 3.hparams.n_head 32
load_ne_hparams 4.hparams.n_head_kv 0
load_ne_hparams 5.hparams.n_layer 32
load_ne_hparams 6.hparams.n_rot 128
load_ne_hparams 7.hparams.ftype 0
load_ne_hparams 8.hparams.max_seq_len 8192
load_ne_hparams 9.hparams.alibi_bias_max 0.000
load_ne_hparams 10.hparams.clip_qkv 0.000
load_ne_hparams 11.hparams.par_res 0
load_ne_hparams 12.hparams.word_embed_proj_dim 0
load_ne_hparams 13.hparams.do_layer_norm_before 0
load_ne_hparams 14.hparams.multi_query_group_num 0
load_ne_hparams 15.hparams.ffn_hidden_size 11008
load_ne_hparams 16.hparams.inner_hidden_size 0
load_ne_hparams 17.hparams.n_experts 0
load_ne_hparams 18.hparams.n_experts_used 0
load_ne_hparams 19.hparams.n_embd_head_k 0
load_ne_hparams 20.hparams.norm_eps 0.000001
load_ne_hparams 21.hparams.freq_base 10000.000
load_ne_hparams 22.hparams.freq_scale 1.000
load_ne_hparams 23.hparams.rope_scaling_factor 0.000
load_ne_hparams 24.hparams.original_max_position_embeddings 0
load_ne_hparams 25.hparams.use_yarn 0
load_ne_vocab 26.vocab.bos_token_id 151643
load_ne_vocab 27.vocab.eos_token_id 151643
load_ne_vocab 28.vocab.pad_token_id -1
load_ne_vocab 29.vocab.sep_token_id -1
beam_size: 1, do_sample: 0, top_k: 40, top_p: 0.950, continuous_batching: 0, max_request_num: 1, early_stopping: 0, scratch_size_ratio: 1.000
Loading the bin file with NE format...
根据给定的文本内容完成以下任务
1. 段落翻译为英文注意词汇底层劳动者、末路鬼的翻译。
2. 给出段落的一句话总结。
3. 给出这段话的情绪关键词列表。文本内容《骆驼祥子》祥子来自农村是个破产的青年农民勤劳、纯朴、善良保留着农村哺育他、教养他的一切却再也不愿意回农村去了。从农村来到城市的祥子渴望以自己的诚实劳动买一辆属于自己的车。做个独立的劳动者是祥子的志愿、希望、甚至是宗教凭着勤劳和坚忍他用三年的时间省吃俭用终于实现了理想成为自食其力的上等车夫。但刚拉半年车就在兵荒马乱中被逃兵掳走祥子失去了洋车只牵回三匹骆驼。祥子没有灰心他依然倔强地从头开始更加克己地拉车攒钱。可是还没有等他再买上车所有的积蓄又被侦探敲诈、洗劫一空买车的梦想再次成泡影。祥子又一次拉上自己的车是以与虎妞成就畸形的婚姻为代价的。可惜好景不长因虎妞死于难产他不得不卖掉人力车去料理丧事。至此他的人生理想彻底破灭了。再加上他心爱的女人小福子的自杀吹熄了他心中最后一朵希望的火花。连遭生活的打击祥子开始丧失了对于生活的任何企求和信心再也无法鼓起生活的勇气不再像从前一样以拉车为自豪他厌恶拉车厌恶劳作。被生活捉弄的祥子开始游戏生活吃喝嫖赌。为了喝酒祥子到处骗钱堕落为“城市垃圾”。最后靠给人干红白喜事做杂工维持生计。祥子由一个“体面的、要强的、好梦想的、利己的、个人的、健壮的、伟大的”底层劳动者沦为一个“堕落的、自私的、不幸的、社会病胎里的产儿个人主义的末路鬼”。以json格式输出任务结果格式规范易于阅读和解析model.cpp: loading model from runtime_outs/ne_qwen_q_nf4_bestla_cfp32_g32.bin
init: n_vocab 151936
init: n_embd 4096
init: n_mult 22016
init: n_head 32
init: n_head_kv 0
init: n_layer 32
init: n_rot 128
init: ftype 0
init: max_seq_len 8192
init: n_ff 11008
init: n_parts 1
load: ctx size 4581.78 MB
load: scratch0 4096.00 MB
load: scratch1 2048.00 MB
load: scratch2 4096.00 MB
load: mem required 14821.78 MB ( memory per state)
......................................................................................
model_init_from_file: support_bestla_kv 0
model_init_from_file: kv self size 256.00 MB。json
{段落翻译: From the countryside to the city, Wang Laozi comes from a rural background, a bankrupt young farmer, hardworking, pure, kind, retaining everything that fed and educated him in the countryside, but no longer willing to return to the countryside. From the countryside to the city, Wang Laozi, who desires to be an independent laborer, hopes, even religion, relies on hard work and perseverance to save money in three years, finally realizing his ideal and becoming an independent laborer. But after half a year, the car was taken away by soldiers in chaos. Wang Laozi lost his foreign car, only taking back three camels. Wang Laozi did not lose heart, he still stubbornly started again, working harder to save money. But before he could buy another car, all his savings were stolen by detectives. The dream of buying a car again became a mirage. Wang Laozi once again bought a car by marrying a deformed woman, Tiger. Unfortunately, it didnt last long, because Tiger died in childbirth, he had to sell his labor car to handle the funeral. At this point, his life ideal was completely shattered. In addition to his beloved woman, Fuyus suicide, he extinguished the last spark of hope in his heart. After being caught in the twists and turns of life, Wang Laozi began to disdain life. He played with life, eating, drinking, gambling. To drink, Wang Laozi went around to beg for money, degenerating into urban garbage. Finally, he supported himself by doing odd jobs for weddings and funerals. Wang Laozi, a respectable, strong, good dreamer, selfish, individualistic, healthy, great lower-level laborer, became a degenerate, selfish, unfortunate, a product of the diseased womb of society, the end of individualism.一句话总结: 祥子由一个体面的、要强的、好梦想的、利己的、个人的、健壮的、伟大的底层劳动者沦为一个堕落的、自私的、不幸的、社会病胎里的产儿个人主义的末路鬼。情绪关键词列表: [绝望, 堕落, 痛苦, 失望, 愤怒, 无奈, 悲哀]
}
|endoftext|# 解码输出
# output_str tokenizer.decode(outputs[0], skip_special_tokensTrue)
# print(Generated text:, output_str)提交指引
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