{"id":812,"date":"2026-07-19T11:19:37","date_gmt":"2026-07-19T03:19:37","guid":{"rendered":"https:\/\/blog.heartwarming.online\/?p=812"},"modified":"2026-07-19T11:19:40","modified_gmt":"2026-07-19T03:19:40","slug":"%e4%bb%8e%e9%9b%b6%e5%9c%a8-linux-%e6%9c%8d%e5%8a%a1%e5%99%a8%e9%83%a8%e7%bd%b2-qwen3-asr-vllm%ef%bc%9a%e4%b8%80%e4%bb%bd%e5%8f%af%e5%a4%8d%e7%94%a8%e7%9a%84%e7%94%b2%e6%96%b9%e7%8e%b0%e5%9c%ba","status":"publish","type":"post","link":"https:\/\/blog.heartwarming.online\/index.php\/2026\/07\/19\/%e4%bb%8e%e9%9b%b6%e5%9c%a8-linux-%e6%9c%8d%e5%8a%a1%e5%99%a8%e9%83%a8%e7%bd%b2-qwen3-asr-vllm%ef%bc%9a%e4%b8%80%e4%bb%bd%e5%8f%af%e5%a4%8d%e7%94%a8%e7%9a%84%e7%94%b2%e6%96%b9%e7%8e%b0%e5%9c%ba\/","title":{"rendered":"\u4ece\u96f6\u5728 Linux \u670d\u52a1\u5668\u90e8\u7f72 Qwen3-ASR + vLLM\uff1a\u4e00\u4efd\u53ef\u590d\u7528\u7684\u7532\u65b9\u73b0\u573a\u5b9e\u6218\u7b14\u8bb0"},"content":{"rendered":"\n
\n

\u672c\u6587\u8bb0\u5f55\u4e86\u4e00\u6b21\u4ece\u201c\u670d\u52a1\u5668\u4e0a\u51e0\u4e4e\u6ca1\u6709\u4e2a\u4eba\u5f00\u53d1\u73af\u5883\u201d\u5f00\u59cb\uff0c\u5b8c\u6210 Linux \u7528\u6237\u9694\u79bb\u3001Miniconda \u5b89\u88c5\u3001\u78c1\u76d8\u8fc1\u79fb\u3001Qwen3-ASR \u4e0e vLLM \u5b89\u88c5\u3001\u6a21\u578b\u542f\u52a8\u3001GPU \u9009\u62e9\u4ee5\u53ca Windows SSH \u96a7\u9053\u8bbf\u95ee\u7684\u5b8c\u6574\u8fc7\u7a0b\u3002<\/p>\n\n\n\n

\u76ee\u6807\u662f\u628a\u4eca\u5929\u8e29\u8fc7\u7684\u5751\u6574\u7406\u6210\u4e00\u5957\u4ee5\u540e\u53ef\u4ee5\u5728\u7532\u65b9\u670d\u52a1\u5668\u590d\u7528\u7684\u90e8\u7f72\u65b9\u6cd5\u3002<\/p>\n\n\n\n

\u672c\u6587\u4e2d\u7684\u7528\u6237\u540d\u3001\u76ee\u5f55\u3001\u7aef\u53e3\u5747\u4e3a\u793a\u4f8b\u3002\u8fdb\u5165\u7532\u65b9\u73af\u5883\u540e\uff0c\u5e94\u6839\u636e\u5bf9\u65b9\u7684\u8d26\u53f7\u5236\u5ea6\u3001\u78c1\u76d8\u89c4\u5212\u3001\u7f51\u7edc\u7b56\u7565\u3001GPU \u8c03\u5ea6\u65b9\u5f0f\u548c\u5b89\u5168\u8981\u6c42\u8fdb\u884c\u8c03\u6574\u3002<\/strong><\/p>\n<\/blockquote>\n\n\n\n

\n\n\n\n

\u4e00\u3001\u6700\u7ec8\u90e8\u7f72\u67b6\u6784<\/h2>\n\n\n\n

\u672c\u6b21\u90e8\u7f72\u5b8c\u6210\u540e\u7684\u94fe\u8def\u5982\u4e0b\uff1a<\/p>\n\n\n\n

Windows \u6d4f\u89c8\u5668\u9ea6\u514b\u98ce\n        \u2193\nWindows \u672c\u5730\u7aef\u53e3\uff0c\u4f8b\u5982 18095\n        \u2193\nSSH \u672c\u5730\u7aef\u53e3\u8f6c\u53d1\n        \u2193\nLinux \u670d\u52a1\u5668 127.0.0.1:10095\n        \u2193\nQwen3-ASR Streaming Demo\n        \u2193\nvLLM \u63a8\u7406\u5f15\u64ce\n        \u2193\n\u6307\u5b9a\u7684 NVIDIA GPU<\/code><\/pre>\n\n\n\n
\u670d\u52a1\u5668\u4fa7\u76ee\u5f55\u89c4\u5212\u4e3a\uff1a<\/p>\n\n\n\n
\/app\/hd\/data01\/username\/\n\u251c\u2500\u2500 conda_envs\/        # Conda \u865a\u62df\u73af\u5883\n\u251c\u2500\u2500 conda_pkgs\/        # Conda \u8f6f\u4ef6\u5305\u7f13\u5b58\n\u251c\u2500\u2500 pip_cache\/         # pip \u4e0b\u8f7d\u7f13\u5b58\n\u251c\u2500\u2500 tmp\/               # pip\u3001\u7f16\u8bd1\u3001\u89e3\u538b\u4e34\u65f6\u76ee\u5f55\n\u251c\u2500\u2500 models\/            # \u6a21\u578b\u6743\u91cd\n\u251c\u2500\u2500 huggingface\/       # Hugging Face \u7f13\u5b58\n\u251c\u2500\u2500 modelscope\/        # ModelScope \u7f13\u5b58\n\u251c\u2500\u2500 torch\/             # PyTorch \u7f13\u5b58\n\u251c\u2500\u2500 projects\/          # \u9879\u76ee\u4ee3\u7801\n\u2514\u2500\u2500 logs\/              # \u8fd0\u884c\u65e5\u5fd7<\/code><\/pre>\n\n\n\n
\u672c\u6b21\u5b9e\u9645\u5360\u7528\u5927\u81f4\u4e3a\uff1a<\/p>\n\n\n\n
Conda \u73af\u5883\u53ca\u63a8\u7406\u6846\u67b6\uff1a\u7ea6 11 GB\nQwen3-ASR \u6a21\u578b\u6743\u91cd\uff1a\u7ea6 1.8 GB\n\u5176\u4ed6\u7f13\u5b58\u548c\u4e34\u65f6\u6587\u4ef6\uff1a\u6570\u767e MB\n\u603b\u8ba1\uff1a\u7ea6 13 GB<\/code><\/pre>\n\n\n\n
\u8fd9\u5c5e\u4e8e\u6b63\u5e38\u73b0\u8c61\u3002\u6a21\u578b\u672c\u8eab\u4e0d\u7b97\u7279\u522b\u5927\uff0c\u4f46 PyTorch\u3001vLLM\u3001Triton\u3001CUDA \u8fd0\u884c\u5e93\u3001cuDNN\u3001cuBLAS\u3001NCCL \u7b49\u4f9d\u8d56\u4f1a\u5360\u636e\u5927\u91cf\u7a7a\u95f4\u3002<\/p>\n\n\n\n
\n\n\n\n
\u4e8c\u3001\u90e8\u7f72\u524d\u5148\u505a\u73af\u5883\u76d8\u70b9<\/h1>\n\n\n\n
\u7532\u65b9\u670d\u52a1\u5668\u4e0a\u4e0d\u8981\u4e00\u4e0a\u6765\u5c31\u5b89\u88c5\u8f6f\u4ef6\u3002\u7b2c\u4e00\u6b65\u5e94\u5148\u786e\u8ba4\u4ee5\u4e0b\u4fe1\u606f\uff1a<\/p>\n\n\n\n
whoami\nhostname\ncat \/etc\/os-release\nuname -m\nfree -h\ndf -h\nnvidia-smi\nwhich srun\nwhich sbatch<\/code><\/pre>\n\n\n\n
\u91cd\u70b9\u786e\u8ba4\uff1a<\/p>\n\n\n\n
    \n
  1. \u5f53\u524d\u767b\u5f55\u8d26\u53f7\u662f\u8c01\uff1b<\/li>\n\n\n\n
  2. \u662f\u5426\u6709 sudo \u6743\u9650\uff1b<\/li>\n\n\n\n
  3. \u64cd\u4f5c\u7cfb\u7edf\u662f Ubuntu\u3001Debian\u3001Rocky Linux \u8fd8\u662f\u5176\u4ed6\u53d1\u884c\u7248\uff1b<\/li>\n\n\n\n
  4. CPU \u67b6\u6784\u662f\u5426\u4e3a x86_64<\/code>\uff1b<\/li>\n\n\n\n
  5. \u6839\u5206\u533a\u548c\u6570\u636e\u76d8\u5269\u4f59\u7a7a\u95f4\uff1b<\/li>\n\n\n\n
  6. GPU \u578b\u53f7\u3001\u6570\u91cf\u548c\u5f53\u524d\u5360\u7528\uff1b<\/li>\n\n\n\n
  7. \u662f\u5426\u5c5e\u4e8e Slurm \u7b49\u96c6\u7fa4\u8c03\u5ea6\u73af\u5883\uff1b<\/li>\n\n\n\n
  8. \u670d\u52a1\u5668\u662f\u5426\u53ef\u4ee5\u8bbf\u95ee\u5916\u7f51\uff1b<\/li>\n\n\n\n
  9. \u662f\u5426\u9700\u8981\u7ecf\u8fc7\u8df3\u677f\u673a\uff1b<\/li>\n\n\n\n
  10. \u7532\u65b9\u662f\u5426\u5141\u8bb8\u81ea\u884c\u521b\u5efa\u7528\u6237\u3001\u5b89\u88c5\u4f9d\u8d56\u548c\u8fd0\u884c\u957f\u671f\u670d\u52a1\u3002<\/li>\n<\/ol>\n\n\n\n
    2.1 \u786e\u8ba4 sudo \u6743\u9650<\/h2>\n\n\n\n
    sudo -l<\/code><\/pre>\n\n\n\n
    \u5982\u679c\u5f53\u524d\u8d26\u53f7\u6ca1\u6709 sudo \u6743\u9650\uff0c\u4e0d\u8981\u5c1d\u8bd5\u7ed5\u8fc7\u6743\u9650\uff0c\u5e94\u8054\u7cfb\u7532\u65b9\u7ba1\u7406\u5458\u6267\u884c\u7cfb\u7edf\u7ea7\u64cd\u4f5c\u3002<\/p>\n\n\n\n
    2.2 \u68c0\u67e5\u78c1\u76d8<\/h2>\n\n\n\n
    df -h\n\ndf -h \"$HOME\"\ndf -h \/tmp<\/code><\/pre>\n\n\n\n
    \u672c\u6b21\u5b9e\u6218\u4e2d\uff0c\u53d1\u73b0\u6839\u5206\u533a\u5df2\u7ecf\u6ee1\u8f7d\uff1a<\/p>\n\n\n\n
    \/dev\/nvme0n1p2  1.8T  1.7T  439M  100%  \/<\/code><\/pre>\n\n\n\n
    \u540c\u65f6\u5b58\u5728\u4e00\u5757\u7a7a\u95f4\u5145\u8db3\u7684\u6570\u636e\u76d8\uff1a<\/p>\n\n\n\n
    \/dev\/sda1  15T  3.1T  11T  22%  \/app\/hd\/data01<\/code><\/pre>\n\n\n\n
    \u56e0\u6b64\u4e0d\u80fd\u7ee7\u7eed\u628a Conda \u73af\u5883\u3001\u6a21\u578b\u548c\u7f13\u5b58\u5199\u5165 \/home<\/code>\uff0c\u5fc5\u987b\u8fc1\u79fb\u5230\u6570\u636e\u76d8\u3002<\/p>\n\n\n\n
    2.3 \u68c0\u67e5 inode \u548c\u7528\u6237\u914d\u989d<\/h2>\n\n\n\n
    \u7a7a\u95f4\u4e0d\u8db3\u4e0d\u4e00\u5b9a\u53ea\u662f\u5bb9\u91cf\u95ee\u9898\uff0c\u4e5f\u53ef\u80fd\u662f inode \u6216\u4e2a\u4eba\u914d\u989d\u8017\u5c3d\uff1a<\/p>\n\n\n\n
    df -i \"$HOME\"\ndf -i \/tmp\nquota -s 2>\/dev\/null || true<\/code><\/pre>\n\n\n\n
    \n\n\n\n
    \u4e09\u3001\u521b\u5efa\u72ec\u7acb Linux \u7528\u6237<\/h1>\n\n\n\n
    \u5728\u5141\u8bb8\u521b\u5efa\u672c\u5730\u7528\u6237\u7684\u666e\u901a\u670d\u52a1\u5668\u4e0a\uff0c\u53ef\u4ee5\u4f7f\u7528\u72ec\u7acb\u8d26\u53f7\u9694\u79bb\u6587\u4ef6\u548c\u5f00\u53d1\u73af\u5883\u3002<\/p>\n\n\n\n
    Ubuntu \/ Debian\uff1a<\/p>\n\n\n\n
    sudo adduser username<\/code><\/pre>\n\n\n\n
    RHEL \/ Rocky \/ AlmaLinux\uff1a<\/p>\n\n\n\n
    sudo useradd --create-home --shell \/bin\/bash username\nsudo passwd username<\/code><\/pre>\n\n\n\n
    \u68c0\u67e5\uff1a<\/p>\n\n\n\n
    id username\nls -ld \/home\/username<\/code><\/pre>\n\n\n\n
    \u5207\u6362\u5230\u65b0\u8d26\u53f7\uff1a<\/p>\n\n\n\n
    sudo su - username<\/code><\/pre>\n\n\n\n
    \u786e\u8ba4\uff1a<\/p>\n\n\n\n
    whoami\npwd\necho \"$HOME\"<\/code><\/pre>\n\n\n\n
    \u5e94\u770b\u5230\uff1a<\/p>\n\n\n\n
    username\n\/home\/username\n\/home\/username<\/code><\/pre>\n\n\n\n
    3.1 \u662f\u5426\u8981\u6388\u4e88 sudo<\/h2>\n\n\n\n
    Ubuntu \/ Debian\uff1a<\/p>\n\n\n\n
    sudo usermod -aG sudo username<\/code><\/pre>\n\n\n\n
    RHEL \u7cfb\u5217\uff1a<\/p>\n\n\n\n
    sudo usermod -aG wheel username<\/code><\/pre>\n\n\n\n
    \u91cd\u65b0\u767b\u5f55\u540e\u9a8c\u8bc1\uff1a<\/p>\n\n\n\n
    sudo whoami<\/code><\/pre>\n\n\n\n
    \u5e94\u8f93\u51fa\uff1a<\/p>\n\n\n\n
    root<\/code><\/pre>\n\n\n\n
    \n
    \u5728\u7532\u65b9\u73b0\u573a\uff0c\u539f\u5219\u4e0a\u9075\u5b88\u6700\u5c0f\u6743\u9650\u3002\u6a21\u578b\u8fd0\u884c\u8d26\u53f7\u901a\u5e38\u4e0d\u9700\u8981\u6c38\u4e45\u5b8c\u6574 sudo \u6743\u9650\u3002\u6700\u597d\u7531\u7ba1\u7406\u5458\u5b8c\u6210\u7cfb\u7edf\u4f9d\u8d56\u5b89\u88c5\uff0c\u800c\u6a21\u578b\u8fdb\u7a0b\u4f7f\u7528\u666e\u901a\u8d26\u53f7\u8fd0\u884c\u3002<\/p>\n<\/blockquote>\n\n\n\n
    \n\n\n\n
    \u56db\u3001\u5b89\u88c5 Miniconda<\/h1>\n\n\n\n
    Miniconda \u5b89\u88c5\u5305\u672c\u8eab\u5df2\u7ecf\u5305\u542b Python\uff0c\u56e0\u6b64\u5373\u4f7f\u670d\u52a1\u5668\u6ca1\u6709 python<\/code> \u547d\u4ee4\uff0c\u4e5f\u53ef\u4ee5\u5b89\u88c5\u3002<\/p>\n\n\n\n
    4.1 \u68c0\u67e5\u67b6\u6784<\/h2>\n\n\n\n
    uname -m<\/code><\/pre>\n\n\n\n
    \u5e38\u89c1\u7ed3\u679c\uff1a<\/p>\n\n\n\n
    x86_64<\/code><\/pre>\n\n\n\n
    4.2 \u4e0b\u8f7d\u6216\u79bb\u7ebf\u4e0a\u4f20<\/h2>\n\n\n\n
    \u670d\u52a1\u5668\u53ef\u8054\u7f51\u65f6\uff1a<\/p>\n\n\n\n
    cd \"$HOME\"\nwget https:\/\/repo.anaconda.com\/miniconda\/Miniconda3-latest-Linux-x86_64.sh<\/code><\/pre>\n\n\n\n
    \u670d\u52a1\u5668\u4e0d\u80fd\u8054\u7f51\u65f6\uff0c\u5728\u672c\u5730\u7535\u8111\u4e0b\u8f7d Linux \u5b89\u88c5\u811a\u672c\uff0c\u7136\u540e\u4e0a\u4f20\uff1a<\/p>\n\n\n\n
    scp \"$HOME\\Downloads\\Miniconda3-latest-Linux-x86_64.sh\" `\n  username@\u670d\u52a1\u5668\u5730\u5740:\/home\/username\/<\/code><\/pre>\n\n\n\n
    \u4f7f\u7528\u975e\u9ed8\u8ba4 SSH \u7aef\u53e3\u65f6\uff1a<\/p>\n\n\n\n
    scp -P 2222 `\n  \"$HOME\\Downloads\\Miniconda3-latest-Linux-x86_64.sh\" `\n  username@\u670d\u52a1\u5668\u5730\u5740:\/home\/username\/<\/code><\/pre>\n\n\n\n
    4.3 \u5b89\u88c5<\/h2>\n\n\n\n
    bash Miniconda3-latest-Linux-x86_64.sh<\/code><\/pre>\n\n\n\n
    \u5b89\u88c5\u76ee\u5f55\u5efa\u8bae\u4fdd\u7559\u4e3a\u5f53\u524d\u7528\u6237\u76ee\u5f55\uff0c\u4f8b\u5982\uff1a<\/p>\n\n\n\n
    \/home\/username\/miniconda3<\/code><\/pre>\n\n\n\n
    \u6700\u540e\u8be2\u95ee\u662f\u5426\u521d\u59cb\u5316 Conda \u65f6\u9009\u62e9\uff1a<\/p>\n\n\n\n
    yes<\/code><\/pre>\n\n\n\n
    \u5b89\u88c5\u5668\u901a\u5e38\u4f1a\u63d0\u793a\uff1a<\/p>\n\n\n\n
    For changes to take effect, close and re-open your current shell.<\/code><\/pre>\n\n\n\n
    \u4e0d\u5fc5\u771f\u7684\u65ad\u5f00 SSH\uff0c\u53ef\u4ee5\u76f4\u63a5\u6267\u884c\uff1a<\/p>\n\n\n\n
    source ~\/.bashrc<\/code><\/pre>\n\n\n\n
    \u5982\u679c conda<\/code> \u4ecd\u627e\u4e0d\u5230\uff1a<\/p>\n\n\n\n
    source ~\/miniconda3\/etc\/profile.d\/conda.sh\nconda init bash\nsource ~\/.bashrc<\/code><\/pre>\n\n\n\n
    \u9a8c\u8bc1\uff1a<\/p>\n\n\n\n
    conda --version\nwhich conda<\/code><\/pre>\n\n\n\n
    4.4 \u5173\u95ed\u81ea\u52a8\u8fdb\u5165 base<\/h2>\n\n\n\n
    conda config --set auto_activate_base false<\/code><\/pre>\n\n\n\n
    \n\n\n\n
    \u4e94\u3001\u5904\u7406 Conda Terms of Service \u63d0\u793a<\/h1>\n\n\n\n
    \u521b\u5efa\u73af\u5883\u65f6\uff0c\u53ef\u80fd\u9047\u5230\uff1a<\/p>\n\n\n\n
    CondaToSNonInteractiveError: Terms of Service have not been accepted<\/code><\/pre>\n\n\n\n
    \u6309\u7167\u63d0\u793a\u63a5\u53d7\u5bf9\u5e94\u9891\u9053\u6761\u6b3e\uff1a<\/p>\n\n\n\n
    conda tos accept \\\n  --override-channels \\\n  --channel https:\/\/repo.anaconda.com\/pkgs\/main\n\nconda tos accept \\\n  --override-channels \\\n  --channel https:\/\/repo.anaconda.com\/pkgs\/r<\/code><\/pre>\n\n\n\n
    \u7136\u540e\u518d\u521b\u5efa\u73af\u5883\u3002<\/p>\n\n\n\n
    \n
    \u5728\u7532\u65b9\u670d\u52a1\u5668\u4e0a\u63a5\u53d7\u4efb\u4f55\u7b2c\u4e09\u65b9\u8f6f\u4ef6\u6761\u6b3e\u524d\uff0c\u5e94\u786e\u8ba4\u7b26\u5408\u7532\u65b9\u91c7\u8d2d\u3001\u6cd5\u52a1\u548c\u8f6f\u4ef6\u8bb8\u53ef\u8981\u6c42\u3002<\/p>\n<\/blockquote>\n\n\n\n
    \n\n\n\n
    \u516d\u3001\u628a\u5927\u6587\u4ef6\u8fc1\u79fb\u5230\u6570\u636e\u76d8<\/h1>\n\n\n\n
    \u672c\u6b21\u6700\u91cd\u8981\u7684\u7ecf\u9a8c\u4e4b\u4e00\u662f\uff1a<\/p>\n\n\n\n
    \n
    \u6a21\u578b\u90e8\u7f72\u524d\u5fc5\u987b\u5148\u89c4\u5212\u78c1\u76d8\u3002\u4e0d\u8981\u9ed8\u8ba4\u628a\u6240\u6709\u5185\u5bb9\u653e\u5728 \/home<\/code>\u3002<\/strong><\/p>\n<\/blockquote>\n\n\n\n
    \u6839\u5206\u533a\u53ea\u6709\u51e0\u767e MB \u5269\u4f59\u65f6\uff0c\u7ee7\u7eed\u5b89\u88c5 vLLM \u4f1a\u76f4\u63a5\u62a5\uff1a<\/p>\n\n\n\n
    OSError: [Errno 28] No space left on device<\/code><\/pre>\n\n\n\n
    6.1 \u521b\u5efa\u4e2a\u4eba\u6570\u636e\u76ee\u5f55<\/h2>\n\n\n\n
    \u4ec5\u521b\u5efa\u81ea\u5df1\u7684\u5b50\u76ee\u5f55\uff1a<\/p>\n\n\n\n
    sudo mkdir -p \/app\/hd\/data01\/username\/{\n  conda_envs,\n  conda_pkgs,\n  pip_cache,\n  tmp,\n  models,\n  huggingface,\n  modelscope,\n  torch,\n  projects,\n  logs\n}<\/code><\/pre>\n\n\n\n
    \u7531\u4e8e Bash \u591a\u884c\u82b1\u62ec\u53f7\u5bb9\u6613\u56e0\u683c\u5f0f\u95ee\u9898\u51fa\u9519\uff0c\u66f4\u7a33\u59a5\u7684\u5199\u6cd5\u662f\uff1a<\/p>\n\n\n\n
    sudo mkdir -p \\\n  \/app\/hd\/data01\/username\/conda_envs \\\n  \/app\/hd\/data01\/username\/conda_pkgs \\\n  \/app\/hd\/data01\/username\/pip_cache \\\n  \/app\/hd\/data01\/username\/tmp \\\n  \/app\/hd\/data01\/username\/models \\\n  \/app\/hd\/data01\/username\/huggingface \\\n  \/app\/hd\/data01\/username\/modelscope \\\n  \/app\/hd\/data01\/username\/torch \\\n  \/app\/hd\/data01\/username\/projects \\\n  \/app\/hd\/data01\/username\/logs<\/code><\/pre>\n\n\n\n
    \u6388\u6743\uff1a<\/p>\n\n\n\n
    sudo chown -R username:username \/app\/hd\/data01\/username\nchmod 700 \/app\/hd\/data01\/username<\/code><\/pre>\n\n\n\n
    \u5fc5\u987b\u7279\u522b\u6ce8\u610f\uff1a<\/p>\n\n\n\n
    # \u9519\u8bef\u793a\u4f8b\uff0c\u53ef\u80fd\u7834\u574f\u6574\u4e2a\u5171\u4eab\u76d8\u6743\u9650\nsudo chown -R username:username \/app\/hd\/data01<\/code><\/pre>\n\n\n\n
    \u53ea\u80fd\u4fee\u6539\u81ea\u5df1\u7684\u5b50\u76ee\u5f55\uff1a<\/p>\n\n\n\n
    sudo chown -R username:username \/app\/hd\/data01\/username<\/code><\/pre>\n\n\n\n
    6.2 \u6d4b\u8bd5\u76ee\u5f55\u5199\u6743\u9650<\/h2>\n\n\n\n
    touch \/app\/hd\/data01\/username\/test_write\nls -l \/app\/hd\/data01\/username\/test_write\nrm \/app\/hd\/data01\/username\/test_write<\/code><\/pre>\n\n\n\n
    \n\n\n\n
    \u4e03\u3001\u914d\u7f6e Conda\u3001pip\u3001\u6a21\u578b\u548c\u4e34\u65f6\u76ee\u5f55<\/h1>\n\n\n\n
    7.1 Conda \u73af\u5883\u4e0e\u5305\u7f13\u5b58<\/h2>\n\n\n\n
    conda config --add envs_dirs \/app\/hd\/data01\/username\/conda_envs\nconda config --add pkgs_dirs \/app\/hd\/data01\/username\/conda_pkgs<\/code><\/pre>\n\n\n\n
    \u9a8c\u8bc1\uff1a<\/p>\n\n\n\n
    conda config --show envs_dirs\nconda config --show pkgs_dirs<\/code><\/pre>\n\n\n\n
    7.2 \u5728 .bashrc<\/code> \u4e2d\u914d\u7f6e\u7f13\u5b58\u8def\u5f84<\/h2>\n\n\n\n
    \u7f16\u8f91\uff1a<\/p>\n\n\n\n
    nano ~\/.bashrc<\/code><\/pre>\n\n\n\n
    \u6dfb\u52a0\uff1a<\/p>\n\n\n\n
    # Personal AI workspace on data disk\nexport AI_DATA_ROOT=\"\/app\/hd\/data01\/username\"\n\nexport TMPDIR=\"$AI_DATA_ROOT\/tmp\"\nexport PIP_CACHE_DIR=\"$AI_DATA_ROOT\/pip_cache\"\n\nexport HF_HOME=\"$AI_DATA_ROOT\/huggingface\"\nexport HUGGINGFACE_HUB_CACHE=\"$AI_DATA_ROOT\/huggingface\/hub\"\nexport TRANSFORMERS_CACHE=\"$AI_DATA_ROOT\/huggingface\/transformers\"\n\nexport MODELSCOPE_CACHE=\"$AI_DATA_ROOT\/modelscope\"\nexport TORCH_HOME=\"$AI_DATA_ROOT\/torch\"<\/code><\/pre>\n\n\n\n
    nano \u4fdd\u5b58\u9000\u51fa<\/h3>\n\n\n\n
    Ctrl + O    \u4fdd\u5b58\nEnter       \u786e\u8ba4\u6587\u4ef6\u540d\nCtrl + X    \u9000\u51fa<\/code><\/pre>\n\n\n\n
    \u52a0\u8f7d\u914d\u7f6e\uff1a<\/p>\n\n\n\n
    source ~\/.bashrc<\/code><\/pre>\n\n\n\n
    \u68c0\u67e5\uff1a<\/p>\n\n\n\n
    echo \"$AI_DATA_ROOT\"\necho \"$TMPDIR\"\necho \"$PIP_CACHE_DIR\"\necho \"$HF_HOME\"\necho \"$MODELSCOPE_CACHE\"\necho \"$TORCH_HOME\"<\/code><\/pre>\n\n\n\n
    \u786e\u4fdd\u76ee\u5f55\u5b58\u5728\uff1a<\/p>\n\n\n\n
    mkdir -p \\\n  \"$AI_DATA_ROOT\/tmp\" \\\n  \"$AI_DATA_ROOT\/pip_cache\" \\\n  \"$AI_DATA_ROOT\/huggingface\/hub\" \\\n  \"$AI_DATA_ROOT\/huggingface\/transformers\" \\\n  \"$AI_DATA_ROOT\/modelscope\" \\\n  \"$AI_DATA_ROOT\/torch\"<\/code><\/pre>\n\n\n\n
    \n\n\n\n
    \u516b\u3001\u91cd\u65b0\u521b\u5efa ASR \u865a\u62df\u73af\u5883<\/h1>\n\n\n\n
    \u4e3a\u4e86\u786e\u4fdd\u73af\u5883\u4e00\u5b9a\u5728\u6570\u636e\u76d8\uff0c\u4f7f\u7528\u5b8c\u6574\u8def\u5f84\u521b\u5efa\uff1a<\/p>\n\n\n\n
    conda create \\\n  --prefix \/app\/hd\/data01\/username\/conda_envs\/qwen3-asr \\\n  python=3.12 \\\n  -y<\/code><\/pre>\n\n\n\n
    \u6fc0\u6d3b\uff1a<\/p>\n\n\n\n
    conda activate \/app\/hd\/data01\/username\/conda_envs\/qwen3-asr<\/code><\/pre>\n\n\n\n
    \u9a8c\u8bc1\uff1a<\/p>\n\n\n\n
    echo \"$CONDA_PREFIX\"\nwhich python\npython --version\ndf -h \"$CONDA_PREFIX\"<\/code><\/pre>\n\n\n\n
    \u6b63\u786e\u7ed3\u679c\u5e94\u6307\u5411\uff1a<\/p>\n\n\n\n
    \/app\/hd\/data01\/username\/conda_envs\/qwen3-asr<\/code><\/pre>\n\n\n\n
    \u4e0d\u8981\u7ee7\u7eed\u4f7f\u7528\u4ecd\u4f4d\u4e8e\u6839\u5206\u533a\u7684\u65e7\u73af\u5883\uff0c\u4f8b\u5982\uff1a<\/p>\n\n\n\n
    \/home\/username\/miniconda3\/envs\/qwen3-asr<\/code><\/pre>\n\n\n\n
    \n\n\n\n
    \u4e5d\u3001\u5b89\u88c5 Qwen3-ASR \u4e0e vLLM<\/h1>\n\n\n\n
    \u5148\u5347\u7ea7\u57fa\u7840\u5de5\u5177\uff1a<\/p>\n\n\n\n
    python -m pip install --upgrade pip setuptools wheel<\/code><\/pre>\n\n\n\n
    \u5b89\u88c5\u6d41\u5f0f ASR \u4f9d\u8d56\uff1a<\/p>\n\n\n\n
    python -m pip install \\\n  --upgrade \\\n  --no-cache-dir \\\n  \"qwen-asr[vllm]\"<\/code><\/pre>\n\n\n\n
    --no-cache-dir<\/code> \u53ef\u4ee5\u51cf\u5c11 pip \u7f13\u5b58\u7684\u91cd\u590d\u5360\u7528\uff0c\u4f46\u5b89\u88c5\u8fc7\u7a0b\u4ecd\u9700\u8981\u4e34\u65f6\u89e3\u538b\u7a7a\u95f4\uff0c\u56e0\u6b64 TMPDIR<\/code> \u5fc5\u987b\u6307\u5411\u5927\u5bb9\u91cf\u6570\u636e\u76d8\u3002<\/p>\n\n\n\n
    9.1 \u4e3a\u4ec0\u4e48\u5b89\u88c5\u5305\u5f88\u5927<\/h2>\n\n\n\n
    \u65e5\u5fd7\u4e2d\u53ef\u80fd\u770b\u5230\uff1a<\/p>\n\n\n\n
    vllm-0.14.0...whl \u7ea6 495 MB<\/code><\/pre>\n\n\n\n
    \u8fd9\u53ea\u662f\u538b\u7f29\u540e\u7684 vLLM Wheel\uff0c\u5e76\u4e0d\u662f\u6a21\u578b\u6743\u91cd\u3002<\/p>\n\n\n\n
    \u6574\u4e2a\u73af\u5883\u8fd8\u5305\u62ec\uff1a<\/p>\n\n\n\n
    Python\nPyTorch\nvLLM\nTriton\nNVIDIA CUDA Runtime\ncuDNN\ncuBLAS\nNCCL\nTransformers\n\u97f3\u9891\u5904\u7406\u4f9d\u8d56\nQwen-ASR Python \u5305<\/code><\/pre>\n\n\n\n
    \u56e0\u6b64\u73af\u5883\u5360\u7528\u7ea6 10 GB \u751a\u81f3\u66f4\u591a\u662f\u6b63\u5e38\u7684\u3002<\/p>\n\n\n\n
    9.2 \u67e5\u770b\u73af\u5883\u4e2d\u6700\u5927\u7684\u5305<\/h2>\n\n\n\n
    du -h \\\n  --max-depth=1 \\\n  \"$CONDA_PREFIX\/lib\/python3.12\/site-packages\" \\\n  2>\/dev\/null | sort -h | tail -n 30<\/code><\/pre>\n\n\n\n
    \u901a\u5e38\u8f83\u5927\u7684\u76ee\u5f55\u5305\u62ec\uff1a<\/p>\n\n\n\n
    nvidia\/\ntorch\/\nvllm\/\ntriton\/\ntransformers\/<\/code><\/pre>\n\n\n\n
    \u4e0d\u8981\u624b\u52a8\u5220\u9664\u8fd9\u4e9b\u76ee\u5f55\uff0c\u5426\u5219\u73af\u5883\u4f1a\u635f\u574f\u3002<\/p>\n\n\n\n
    \n\n\n\n
    \u5341\u3001\u9a8c\u8bc1 PyTorch \u548c GPU<\/h1>\n\n\n\n
    python - <<'PY'\nimport torch\n\nprint(\"PyTorch:\", torch.__version__)\nprint(\"PyTorch CUDA:\", torch.version.cuda)\nprint(\"CUDA available:\", torch.cuda.is_available())\nprint(\"GPU count:\", torch.cuda.device_count())\n\nfor index in range(torch.cuda.device_count()):\n    print(index, torch.cuda.get_device_name(index))\nPY<\/code><\/pre>\n\n\n\n
    \u9884\u671f\uff1a<\/p>\n\n\n\n
    CUDA available: True<\/code><\/pre>\n\n\n\n
    \u5982\u679c\u4e3a False<\/code>\uff0c\u68c0\u67e5\uff1a<\/p>\n\n\n\n
    nvidia-smi\necho \"$CUDA_VISIBLE_DEVICES\"<\/code><\/pre>\n\n\n\n
    \u5728 Slurm \u73af\u5883\u4e2d\uff0c\u8fd8\u8981\u786e\u8ba4\u5f53\u524d Shell \u662f\u5426\u771f\u7684\u7533\u8bf7\u5230\u4e86 GPU\u3002<\/p>\n\n\n\n
    \n\n\n\n
    \u5341\u4e00\u3001\u4e0b\u8f7d\u6a21\u578b\u6743\u91cd<\/h1>\n\n\n\n
    \u6a21\u578b\u76ee\u5f55\u653e\u5728\u6570\u636e\u76d8\uff1a<\/p>\n\n\n\n
    mkdir -p \/app\/hd\/data01\/username\/models\/Qwen3-ASR-0.6B<\/code><\/pre>\n\n\n\n
    \u53ef\u4ee5\u901a\u8fc7 ModelScope \u4e0b\u8f7d\uff1a<\/p>\n\n\n\n
    python -m pip install --upgrade modelscope\n\nmodelscope download \\\n  --model Qwen\/Qwen3-ASR-0.6B \\\n  --local_dir \/app\/hd\/data01\/username\/models\/Qwen3-ASR-0.6B<\/code><\/pre>\n\n\n\n
    \u68c0\u67e5\uff1a<\/p>\n\n\n\n
    du -sh \/app\/hd\/data01\/username\/models\/Qwen3-ASR-0.6B\nls -lh \/app\/hd\/data01\/username\/models\/Qwen3-ASR-0.6B<\/code><\/pre>\n\n\n\n
    \u672c\u6b21\u6a21\u578b\u76ee\u5f55\u7ea6\u4e3a 1.8 GB\u3002<\/p>\n\n\n\n
    \n\n\n\n
    \u5341\u4e8c\u3001\u542f\u52a8\u6d41\u5f0f ASR \u670d\u52a1<\/h1>\n\n\n\n
    12.1 \u542f\u52a8\u524d\u5148\u770b GPU<\/h2>\n\n\n\n
    nvidia-smi\n\nnvidia-smi \\\n  --query-gpu=index,name,memory.total,memory.used,memory.free,utilization.gpu \\\n  --format=csv<\/code><\/pre>\n\n\n\n
    \u518d\u770b\u6bcf\u5f20\u5361\u4e0a\u7684\u8fdb\u7a0b\uff1a<\/p>\n\n\n\n
    nvidia-smi pmon -c 1<\/code><\/pre>\n\n\n\n
    \u67e5\u770b\u8fdb\u7a0b\u5c5e\u4e8e\u54ea\u4e2a\u7528\u6237\uff1a<\/p>\n\n\n\n
    ps -o user,pid,ppid,etime,cmd -p \u8fdb\u7a0bPID<\/code><\/pre>\n\n\n\n
    \u4e0d\u8981\u7ed3\u675f\u4e0d\u5c5e\u4e8e\u81ea\u5df1\u7684 GPU \u8fdb\u7a0b\u3002<\/p>\n\n\n\n
    12.2 \u6307\u5b9a\u5355\u5f20 GPU<\/h2>\n\n\n\n
    \u5047\u8bbe GPU 5 \u7a7a\u95f2\uff1a<\/p>\n\n\n\n
    CUDA_VISIBLE_DEVICES=5 \\\nqwen-asr-demo-streaming \\\n  --asr-model-path \/app\/hd\/data01\/username\/models\/Qwen3-ASR-0.6B \\\n  --gpu-memory-utilization 0.60 \\\n  --host 127.0.0.1 \\\n  --port 10095<\/code><\/pre>\n\n\n\n
    \u6216\u8005\u5148\u5bfc\u51fa\u53d8\u91cf\uff1a<\/p>\n\n\n\n
    export CUDA_VISIBLE_DEVICES=5<\/code><\/pre>\n\n\n\n
    \u518d\u542f\u52a8\uff1a<\/p>\n\n\n\n
    qwen-asr-demo-streaming \\\n  --asr-model-path \/app\/hd\/data01\/username\/models\/Qwen3-ASR-0.6B \\\n  --gpu-memory-utilization 0.60 \\\n  --host 127.0.0.1 \\\n  --port 10095<\/code><\/pre>\n\n\n\n
    \u9700\u8981\u6ce8\u610f\uff1a<\/p>\n\n\n\n
    \u7269\u7406 GPU 5\n    \u2193 CUDA_VISIBLE_DEVICES=5\n\u7a0b\u5e8f\u5185\u90e8\u901a\u5e38\u663e\u793a\u4e3a\u903b\u8f91 cuda:0<\/code><\/pre>\n\n\n\n
    \u56e0\u6b64\u65e5\u5fd7\u91cc\u51fa\u73b0 cuda:0<\/code> \u4e0d\u4ee3\u8868\u771f\u7684\u5360\u7528\u7269\u7406 GPU 0\uff0c\u5e94\u4ee5 nvidia-smi<\/code> \u4e3a\u51c6\u3002<\/p>\n\n\n\n
    12.3 \u6210\u529f\u65e5\u5fd7<\/h2>\n\n\n\n
    \u6210\u529f\u542f\u52a8\u65f6\u53ef\u770b\u5230\uff1a<\/p>\n\n\n\n
    Supported tasks: ['generate', 'transcription']\nModel loaded.\nRunning on http:\/\/127.0.0.1:10095<\/code><\/pre>\n\n\n\n
    \u770b\u5230\uff1a<\/p>\n\n\n\n
    Capturing CUDA graphs...\nGraph capturing finished...<\/code><\/pre>\n\n\n\n
    \u8bf4\u660e vLLM \u6b63\u5728\u521d\u59cb\u5316 CUDA Graph \u548c\u63a8\u7406\u7f13\u5b58\uff0c\u5c5e\u4e8e\u6b63\u5e38\u8fc7\u7a0b\u3002<\/p>\n\n\n\n
    12.4 Flask \u5f00\u53d1\u670d\u52a1\u5668\u8b66\u544a<\/h2>\n\n\n\n
    \u5b98\u65b9 Demo \u53ef\u80fd\u63d0\u793a\uff1a<\/p>\n\n\n\n
    WARNING: This is a development server.\nDo not use it in a production deployment.<\/code><\/pre>\n\n\n\n
    \u5f53\u524d\u6d4b\u8bd5\u9636\u6bb5\u53ef\u4ee5\u63a5\u53d7\uff0c\u56e0\u4e3a\u670d\u52a1\u53ea\u76d1\u542c\uff1a<\/p>\n\n\n\n
    127.0.0.1<\/code><\/pre>\n\n\n\n
    \u5e76\u901a\u8fc7 SSH \u96a7\u9053\u8bbf\u95ee\u3002<\/p>\n\n\n\n
    \u7532\u65b9\u6b63\u5f0f\u751f\u4ea7\u90e8\u7f72\u65f6\uff0c\u5e94\u589e\u52a0\uff1a<\/p>\n\n\n\n
      \n
    • systemd \u6216 Supervisor \u8fdb\u7a0b\u6258\u7ba1\uff1b<\/li>\n\n\n\n
    • \u751f\u4ea7\u7ea7 API \u670d\u52a1\uff1b<\/li>\n\n\n\n
    • \u9274\u6743\uff1b<\/li>\n\n\n\n
    • HTTPS \u6216\u5185\u7f51\u53cd\u5411\u4ee3\u7406\uff1b<\/li>\n\n\n\n
    • \u65e5\u5fd7\u8f6e\u8f6c\uff1b<\/li>\n\n\n\n
    • \u5065\u5eb7\u68c0\u67e5\uff1b<\/li>\n\n\n\n
    • \u8d85\u65f6\u4e0e\u5e76\u53d1\u9650\u5236\uff1b<\/li>\n\n\n\n
    • GPU \u8d44\u6e90\u9694\u79bb\uff1b<\/li>\n\n\n\n
    • \u670d\u52a1\u542f\u52a8\u3001\u505c\u6b62\u548c\u56de\u6eda\u811a\u672c\u3002<\/li>\n<\/ul>\n\n\n\n
      \n\n\n\n
      \u5341\u4e09\u3001\u76d1\u63a7 GPU<\/h1>\n\n\n\n
      \u53e6\u5f00\u4e00\u4e2a SSH \u7a97\u53e3\uff1a<\/p>\n\n\n\n
      watch -n 1 nvidia-smi<\/code><\/pre>\n\n\n\n
      \u53ea\u770b\u6307\u5b9a GPU\uff1a<\/p>\n\n\n\n
      watch -n 1 nvidia-smi -i 5<\/code><\/pre>\n\n\n\n
      \u67e5\u8be2\u7b80\u6d01\u72b6\u6001\uff1a<\/p>\n\n\n\n
      nvidia-smi \\\n  --query-gpu=index,name,memory.used,memory.free,utilization.gpu \\\n  --format=csv,noheader<\/code><\/pre>\n\n\n\n
      \u672c\u6b21\u670d\u52a1\u5668\u6709\u591a\u5f20 3090 \u548c 4090\uff0c\u5b9e\u9645\u8f93\u51fa\u663e\u793a\uff1a<\/p>\n\n\n\n
        \n
      • GPU 1\u3001GPU 4 \u6709\u5176\u4ed6\u5b9e\u9a8c\uff1b<\/li>\n\n\n\n
      • GPU 2 \u5df2\u88ab\u672c\u6b21 vLLM \u670d\u52a1\u5360\u7528\uff1b<\/li>\n\n\n\n
      • GPU 0\u30013\u30015\u30016 \u76f8\u5bf9\u7a7a\u95f2\uff1b<\/li>\n\n\n\n
      • \u65b0\u6d4b\u8bd5\u4f18\u5148\u9009\u62e9\u7a7a\u95f2\u7684 GPU 5\uff1b<\/li>\n\n\n\n
      • 0.6B \u6a21\u578b\u4e5f\u53ef\u4ee5\u5728\u7a7a\u95f2\u7684 3090 \u4e0a\u6d4b\u8bd5\u3002<\/li>\n<\/ul>\n\n\n\n
        \u4e0d\u8981\u53ea\u770b GPU-Util=0%<\/code>\u3002vLLM \u5728\u7a7a\u95f2\u7b49\u5f85\u8bf7\u6c42\u65f6\u5229\u7528\u7387\u53ef\u80fd\u662f 0%\uff0c\u4f46\u663e\u5b58\u5df2\u7ecf\u9884\u7559\u3002<\/p>\n\n\n\n
        \n\n\n\n
        \u5341\u56db\u3001Windows \u901a\u8fc7 SSH \u96a7\u9053\u8bbf\u95ee<\/h1>\n\n\n\n
        \u670d\u52a1\u5668\u76d1\u542c\uff1a<\/p>\n\n\n\n
        127.0.0.1:10095<\/code><\/pre>\n\n\n\n
        \u8fd9\u610f\u5473\u7740\u5916\u90e8\u7535\u8111\u4e0d\u80fd\u76f4\u63a5\u8bbf\u95ee\uff0c\u9700\u8981 SSH \u7aef\u53e3\u8f6c\u53d1\u3002<\/p>\n\n\n\n
        14.1 \u666e\u901a\u8fde\u63a5<\/h2>\n\n\n\n
        \u5728 Windows PowerShell \u6267\u884c\uff1a<\/p>\n\n\n\n
        ssh -N `\n  -L 127.0.0.1:18095:127.0.0.1:10095 `\n  username@\u670d\u52a1\u5668\u5730\u5740<\/code><\/pre>\n\n\n\n
        \u7136\u540e\u6d4f\u89c8\u5668\u6253\u5f00\uff1a<\/p>\n\n\n\n
        http://127.0.0.1:18095<\/code><\/pre>\n\n\n\n
        \u6620\u5c04\u5173\u7cfb\uff1a<\/p>\n\n\n\n
        Windows 127.0.0.1:18095\n        \u2193\nLinux \u670d\u52a1\u5668 127.0.0.1:10095<\/code><\/pre>\n\n\n\n
        \u672c\u5730\u7aef\u53e3\u4e0d\u9700\u8981\u548c\u670d\u52a1\u5668\u7aef\u53e3\u76f8\u540c\u3002<\/p>\n\n\n\n
        14.2 \u591a\u4e2a\u670d\u52a1<\/h2>\n\n\n\n
        ssh -N `\n  -L 127.0.0.1:18095:127.0.0.1:10095 `\n  -L 127.0.0.1:18096:127.0.0.1:10096 `\n  username@\u670d\u52a1\u5668\u5730\u5740<\/code><\/pre>\n\n\n\n
        \u8bbf\u95ee\uff1a<\/p>\n\n\n\n
        http://127.0.0.1:18095\nhttp:\/\/127.0.0.1:18096<\/code><\/pre>\n\n\n\n
        14.3 \u7ecf\u8fc7\u8df3\u677f\u673a<\/h2>\n\n\n\n
        ssh -N `\n  -J \u5165\u53e3\u7528\u6237\u540d@\u5165\u53e3\u670d\u52a1\u5668\u5730\u5740 `\n  -L 127.0.0.1:18095:127.0.0.1:10095 `\n  username@app01<\/code><\/pre>\n\n\n\n
        14.4 Windows \u51fa\u73b0 Permission denied<\/h2>\n\n\n\n
        \u672c\u6b21\u9047\u5230\uff1a<\/p>\n\n\n\n
        bind [127.0.0.1]:10095: Permission denied\nbind [127.0.0.1]:10096: Permission denied<\/code><\/pre>\n\n\n\n
        \u8fd9\u901a\u5e38\u662f Windows \u672c\u5730\u7aef\u53e3\u88ab\u5360\u7528\u6216\u5904\u4e8e\u7cfb\u7edf\u4fdd\u7559\u7aef\u53e3\u8303\u56f4\uff0c\u4e0d\u662f\u670d\u52a1\u5668\u6a21\u578b\u670d\u52a1\u62d2\u7edd\u8fde\u63a5\u3002<\/p>\n\n\n\n
        \u5904\u7406\u65b9\u6cd5\u662f\u6362\u672c\u5730\u7aef\u53e3\uff1a<\/p>\n\n\n\n
        ssh -N `\n  -L 18095:127.0.0.1:10095 `\n  username@\u670d\u52a1\u5668\u5730\u5740<\/code><\/pre>\n\n\n\n
        \u68c0\u67e5\u7aef\u53e3\u5360\u7528\uff1a<\/p>\n\n\n\n
        Get-NetTCPConnection `\n  -LocalPort 10095,10096 `\n  -ErrorAction SilentlyContinue<\/code><\/pre>\n\n\n\n
        \u67e5\u770b Windows \u4fdd\u7559\u7aef\u53e3\u8303\u56f4\uff1a<\/p>\n\n\n\n
        netsh interface ipv4 show excludedportrange protocol=tcp<\/code><\/pre>\n\n\n\n
        \u4e0d\u8981\u968f\u610f\u5220\u9664 Windows \u7cfb\u7edf\u4fdd\u7559\u7aef\u53e3\uff0c\u76f4\u63a5\u6362\u7528 18095<\/code>\u300118096<\/code> \u7b49\u7aef\u53e3\u66f4\u5b89\u5168\u3002<\/p>\n\n\n\n
        \u9a8c\u8bc1\u672c\u5730\u96a7\u9053\uff1a<\/p>\n\n\n\n
        Test-NetConnection 127.0.0.1 -Port 18095<\/code><\/pre>\n\n\n\n
        \u5e94\u770b\u5230\uff1a<\/p>\n\n\n\n
        TcpTestSucceeded : True<\/code><\/pre>\n\n\n\n
        \n\n\n\n
        \u5341\u4e94\u3001\u5e38\u89c1\u9519\u8bef\u4e0e\u5904\u7406<\/h1>\n\n\n\n
        15.1 conda: command not found<\/code><\/h2>\n\n\n\n
        source ~\/.bashrc<\/code><\/pre>\n\n\n\n
        \u4ecd\u5931\u8d25\uff1a<\/p>\n\n\n\n
        source ~\/miniconda3\/etc\/profile.d\/conda.sh\nconda init bash\nsource ~\/.bashrc<\/code><\/pre>\n\n\n\n
        15.2 Conda \u6761\u6b3e\u672a\u63a5\u53d7<\/h2>\n\n\n\n
        conda tos accept \\\n  --override-channels \\\n  --channel https:\/\/repo.anaconda.com\/pkgs\/main\n\nconda tos accept \\\n  --override-channels \\\n  --channel https:\/\/repo.anaconda.com\/pkgs\/r<\/code><\/pre>\n\n\n\n
        15.3 No space left on device<\/code><\/h2>\n\n\n\n
        df -h\ndf -h \"$HOME\"\ndf -h \/tmp\ndf -i \"$HOME\"\nquota -s 2>\/dev\/null || true<\/code><\/pre>\n\n\n\n
        \u6e05\u7406\u81ea\u5df1\u7684\u7f13\u5b58\uff1a<\/p>\n\n\n\n
        conda clean --all -y\npython -m pip cache purge\nrm -rf ~\/.cache\/pip<\/code><\/pre>\n\n\n\n
        \u4f46\u6839\u672c\u89e3\u51b3\u65b9\u6848\u662f\u628a\u73af\u5883\u3001\u7f13\u5b58\u3001\u4e34\u65f6\u6587\u4ef6\u548c\u6a21\u578b\u8fc1\u79fb\u5230\u5927\u5bb9\u91cf\u6570\u636e\u76d8\u3002<\/p>\n\n\n\n
        15.4 \u5b89\u88c5\u5931\u8d25\u540e\u73af\u5883\u53ef\u80fd\u4e0d\u5b8c\u6574<\/h2>\n\n\n\n
        python -m pip check<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u4f9d\u8d56\u6df7\u4e71\uff0c\u91cd\u5efa\u73af\u5883\u6bd4\u624b\u5de5\u4fee\u590d\u66f4\u53ef\u9760\u3002<\/p>\n\n\n\n
        15.5 GPU \u88ab\u522b\u4eba\u5360\u7528<\/h2>\n\n\n\n
        nvidia-smi\nnvidia-smi pmon -c 1\nps -o user,pid,etime,cmd -p PID<\/code><\/pre>\n\n\n\n
        \u505c\u6b62\u81ea\u5df1\u7684\u670d\u52a1\uff1a<\/p>\n\n\n\n
        Ctrl + C<\/code><\/pre>\n\n\n\n
        \u7136\u540e\u6307\u5b9a\u7a7a\u95f2 GPU\uff1a<\/p>\n\n\n\n
        CUDA_VISIBLE_DEVICES=5 qwen-asr-demo-streaming ...<\/code><\/pre>\n\n\n\n
        15.6 \u670d\u52a1\u7aef\u53e3\u5df2\u5360\u7528<\/h2>\n\n\n\n
        ss -lntp | grep 10095<\/code><\/pre>\n\n\n\n
        \u6362\u7aef\u53e3\uff1a<\/p>\n\n\n\n
        --port 10096<\/code><\/pre>\n\n\n\n
        15.7 CUDA \u4e0d\u53ef\u7528<\/h2>\n\n\n\n
        nvidia-smi\npython -c \"import torch; print(torch.cuda.is_available())\"\necho \"$CUDA_VISIBLE_DEVICES\"<\/code><\/pre>\n\n\n\n
        \u5728 Slurm \u96c6\u7fa4\u4e2d\uff0c\u5148\u901a\u8fc7\u8c03\u5ea6\u5668\u7533\u8bf7 GPU\uff0c\u4e0d\u8981\u5728\u767b\u5f55\u8282\u70b9\u76f4\u63a5\u8fd0\u884c\u6a21\u578b\u3002<\/p>\n\n\n\n
        \n\n\n\n
        \u5341\u516d\u3001\u7a7a\u95f4\u4e0e\u7f13\u5b58\u68c0\u67e5\u547d\u4ee4<\/h1>\n\n\n\n
        \u67e5\u770b\u603b\u5360\u7528\uff1a<\/p>\n\n\n\n
        du -h --max-depth=1 \/app\/hd\/data01\/username | sort -h<\/code><\/pre>\n\n\n\n
        \u67e5\u770b\u5f53\u524d\u73af\u5883\u5927\u5c0f\uff1a<\/p>\n\n\n\n
        du -sh \"$CONDA_PREFIX\"<\/code><\/pre>\n\n\n\n
        \u67e5\u770b\u6a21\u578b\u5927\u5c0f\uff1a<\/p>\n\n\n\n
        du -sh \/app\/hd\/data01\/username\/models\/*<\/code><\/pre>\n\n\n\n
        \u67e5\u770b\u6700\u5927\u7684\u6587\u4ef6\uff1a<\/p>\n\n\n\n
        du -ah \/app\/hd\/data01\/username \\\n  2>\/dev\/null | sort -rh | head -n 30<\/code><\/pre>\n\n\n\n
        \u67e5\u770b\u6839\u5206\u533a\u662f\u8c01\u5360\u6ee1\u7684\uff0c\u4ec5\u505a\u6392\u67e5\uff0c\u4e0d\u8981\u968f\u610f\u5220\u9664\uff1a<\/p>\n\n\n\n
        sudo du -xhd1 \/ 2>\/dev\/null | sort -h\nsudo du -xhd1 \/var 2>\/dev\/null | sort -h\nsudo du -xhd1 \/home 2>\/dev\/null | sort -h\nsudo journalctl --disk-usage<\/code><\/pre>\n\n\n\n
        \n\n\n\n
        \u5341\u4e03\u3001\u7532\u65b9\u73b0\u573a\u90e8\u7f72\u5efa\u8bae<\/h1>\n\n\n\n
        \u4eca\u5929\u7684\u5b9e\u9a8c\u73af\u5883\u53ef\u4ee5\u4f7f\u7528 Demo \u5feb\u901f\u9a8c\u8bc1\uff0c\u4f46\u8fdb\u5165\u7532\u65b9\u670d\u52a1\u5668\u65f6\uff0c\u5e94\u6309\u7167\u66f4\u4e25\u683c\u7684\u6d41\u7a0b\u6267\u884c\u3002<\/p>\n\n\n\n
        17.1 \u90e8\u7f72\u524d\u786e\u8ba4\u6e05\u5355<\/h2>\n\n\n\n
          \n
        • [ ] \u83b7\u5f97\u4e66\u9762\u6216\u660e\u786e\u7684\u7cfb\u7edf\u64cd\u4f5c\u6388\u6743\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u64cd\u4f5c\u7cfb\u7edf\u7248\u672c\u548c CPU \u67b6\u6784\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4 NVIDIA \u9a71\u52a8\u4e0e GPU \u53ef\u89c1\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4 CUDA \u517c\u5bb9\u5173\u7cfb\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u662f\u5426\u4f7f\u7528 Docker\u3001Conda \u6216\u79bb\u7ebf\u5b89\u88c5\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u6839\u5206\u533a\u3001\u6570\u636e\u76d8\u548c\u7528\u6237\u914d\u989d\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u6a21\u578b\u6587\u4ef6\u5141\u8bb8\u5b58\u653e\u7684\u4f4d\u7f6e\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u670d\u52a1\u5668\u662f\u5426\u5141\u8bb8\u8bbf\u95ee\u516c\u7f51\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u662f\u5426\u9700\u8981\u4ee3\u7406\u3001\u955c\u50cf\u6e90\u6216\u79bb\u7ebf\u8f6f\u4ef6\u5305\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u662f\u5426\u4e3a Slurm\u3001Kubernetes \u6216\u5176\u4ed6\u8c03\u5ea6\u73af\u5883\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u7aef\u53e3\u3001\u9632\u706b\u5899\u3001\u53cd\u5411\u4ee3\u7406\u548c\u8bbf\u95ee\u63a7\u5236\u8981\u6c42\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u65e5\u5fd7\u4fdd\u5b58\u5468\u671f\u548c\u6570\u636e\u8131\u654f\u8981\u6c42\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u6a21\u578b\u8bb8\u53ef\u548c\u7b2c\u4e09\u65b9\u8f6f\u4ef6\u6761\u6b3e\uff1b<\/li>\n\n\n\n
        • [ ] \u786e\u8ba4\u5907\u4efd\u548c\u56de\u6eda\u65b9\u6848\u3002<\/li>\n<\/ul>\n\n\n\n
          17.2 \u76ee\u5f55\u89c4\u8303<\/h2>\n\n\n\n
          \u5efa\u8bae\u7edf\u4e00\u4e3a\uff1a<\/p>\n\n\n\n
          \/data\/<project>\/\n\u251c\u2500\u2500 envs\/\n\u251c\u2500\u2500 models\/\n\u251c\u2500\u2500 cache\/\n\u251c\u2500\u2500 tmp\/\n\u251c\u2500\u2500 app\/\n\u251c\u2500\u2500 logs\/\n\u2514\u2500\u2500 scripts\/<\/code><\/pre>\n\n\n\n
          \u4e0d\u8981\u628a\u5927\u6a21\u578b\u548c\u63a8\u7406\u6846\u67b6\u9ed8\u8ba4\u88c5\u8fdb\u6839\u5206\u533a\u3002<\/p>\n\n\n\n
          17.3 \u5b89\u5168\u539f\u5219<\/h2>\n\n\n\n
            \n
          1. \u6a21\u578b\u670d\u52a1\u4f7f\u7528\u666e\u901a\u7528\u6237\u8fd0\u884c\uff1b<\/li>\n\n\n\n
          2. \u5b89\u88c5 Python \u5305\u65f6\u4e0d\u4f7f\u7528 sudo pip<\/code>\uff1b<\/li>\n\n\n\n
          3. \u4e0d\u9012\u5f52\u4fee\u6539\u5171\u4eab\u76d8\u7236\u76ee\u5f55\u6743\u9650\uff1b<\/li>\n\n\n\n
          4. \u6d4b\u8bd5\u670d\u52a1\u4f18\u5148\u76d1\u542c 127.0.0.1<\/code>\uff1b<\/li>\n\n\n\n
          5. \u5bf9\u5916\u66b4\u9732\u65f6\u5fc5\u987b\u589e\u52a0\u9274\u6743\u548c\u7f51\u7edc\u8bbf\u95ee\u63a7\u5236\uff1b<\/li>\n\n\n\n
          6. \u4e0d\u5728\u65e5\u5fd7\u4e2d\u6253\u5370\u5bc6\u94a5\u3001Token\u3001\u7528\u6237\u97f3\u9891\u6216\u654f\u611f\u4e1a\u52a1\u6570\u636e\uff1b<\/li>\n\n\n\n
          7. \u4e0d\u6740\u6b7b\u5176\u4ed6\u7528\u6237\u6216\u5176\u4ed6\u4e1a\u52a1\u7684 GPU \u8fdb\u7a0b\uff1b<\/li>\n\n\n\n
          8. \u4f7f\u7528\u8c03\u5ea6\u7cfb\u7edf\u65f6\u5fc5\u987b\u901a\u8fc7\u8c03\u5ea6\u5668\u7533\u8bf7\u8d44\u6e90\uff1b<\/li>\n\n\n\n
          9. \u6240\u6709\u914d\u7f6e\u53d8\u66f4\u5e94\u53ef\u8ffd\u6eaf\u3001\u53ef\u56de\u6eda\uff1b<\/li>\n\n\n\n
          10. \u751f\u4ea7\u73af\u5883\u4e0d\u76f4\u63a5\u4f7f\u7528\u5f00\u53d1\u670d\u52a1\u5668\u3002<\/li>\n<\/ol>\n\n\n\n
            17.4 \u8d44\u6e90\u63a7\u5236<\/h2>\n\n\n\n
            \u542f\u52a8\u524d\u660e\u786e\u6307\u5b9a\uff1a<\/p>\n\n\n\n
            CUDA_VISIBLE_DEVICES=<GPU\u7f16\u53f7><\/code><\/pre>\n\n\n\n
            \u5e76\u4ece\u8f83\u4f4e\u663e\u5b58\u5229\u7528\u7387\u5f00\u59cb\uff1a<\/p>\n\n\n\n
            --gpu-memory-utilization 0.50<\/code><\/pre>\n\n\n\n
            \u786e\u8ba4\u7a33\u5b9a\u540e\u518d\u8c03\u6574\u5230\uff1a<\/p>\n\n\n\n
            0.60\n0.70<\/code><\/pre>\n\n\n\n
            \u4e0d\u8981\u5728\u5171\u4eab\u670d\u52a1\u5668\u4e0a\u76f4\u63a5\u8bbe\u7f6e\u8fc7\u9ad8\u6bd4\u4f8b\u3002<\/p>\n\n\n\n
            \n\n\n\n
            \u5341\u516b\u3001\u5efa\u8bae\u4fdd\u5b58\u7684\u542f\u52a8\u811a\u672c<\/h1>\n\n\n\n
            \u521b\u5efa\uff1a<\/p>\n\n\n\n
            nano \/app\/hd\/data01\/username\/projects\/start_qwen_asr.sh<\/code><\/pre>\n\n\n\n
            \u5185\u5bb9\uff1a<\/p>\n\n\n\n
            #!\/usr\/bin\/env bash\nset -euo pipefail\n\nDATA_ROOT=\"\/app\/hd\/data01\/username\"\nENV_PATH=\"$DATA_ROOT\/conda_envs\/qwen3-asr\"\nMODEL_PATH=\"$DATA_ROOT\/models\/Qwen3-ASR-0.6B\"\nGPU_ID=\"${GPU_ID:-5}\"\nPORT=\"${PORT:-10095}\"\nGPU_MEMORY_UTILIZATION=\"${GPU_MEMORY_UTILIZATION:-0.60}\"\n\nexport TMPDIR=\"$DATA_ROOT\/tmp\"\nexport PIP_CACHE_DIR=\"$DATA_ROOT\/pip_cache\"\nexport HF_HOME=\"$DATA_ROOT\/huggingface\"\nexport MODELSCOPE_CACHE=\"$DATA_ROOT\/modelscope\"\nexport TORCH_HOME=\"$DATA_ROOT\/torch\"\nexport CUDA_VISIBLE_DEVICES=\"$GPU_ID\"\n\nsource \"$HOME\/miniconda3\/etc\/profile.d\/conda.sh\"\nconda activate \"$ENV_PATH\"\n\nexec qwen-asr-demo-streaming \\\n  --asr-model-path \"$MODEL_PATH\" \\\n  --gpu-memory-utilization \"$GPU_MEMORY_UTILIZATION\" \\\n  --host 127.0.0.1 \\\n  --port \"$PORT\"<\/code><\/pre>\n\n\n\n
            \u8d4b\u4e88\u6267\u884c\u6743\u9650\uff1a<\/p>\n\n\n\n
            chmod +x \/app\/hd\/data01\/username\/projects\/start_qwen_asr.sh<\/code><\/pre>\n\n\n\n
            \u8fd0\u884c\uff1a<\/p>\n\n\n\n
            \/app\/hd\/data01\/username\/projects\/start_qwen_asr.sh<\/code><\/pre>\n\n\n\n
            \u4e34\u65f6\u6307\u5b9a GPU \u548c\u7aef\u53e3\uff1a<\/p>\n\n\n\n
            GPU_ID=6 PORT=10096 \\\n  \/app\/hd\/data01\/username\/projects\/start_qwen_asr.sh<\/code><\/pre>\n\n\n\n
            \n\n\n\n
            \u5341\u4e5d\u3001\u5efa\u8bae\u4fdd\u5b58\u7684\u73af\u5883\u68c0\u67e5\u811a\u672c<\/h1>\n\n\n\n
            \u521b\u5efa\uff1a<\/p>\n\n\n\n
            nano \/app\/hd\/data01\/username\/projects\/check_server.sh<\/code><\/pre>\n\n\n\n
            \u5185\u5bb9\uff1a<\/p>\n\n\n\n
            #!\/usr\/bin\/env bash\nset -u\n\necho \"===== Identity =====\"\nwhoami\nhostname\n\necho\necho \"===== OS =====\"\ncat \/etc\/os-release 2>\/dev\/null || true\nuname -m\n\necho\necho \"===== Memory =====\"\nfree -h\n\necho\necho \"===== Filesystems =====\"\ndf -h\n\necho\necho \"===== Home =====\"\necho \"$HOME\"\ndf -h \"$HOME\"\n\necho\necho \"===== GPU =====\"\nnvidia-smi || true\n\necho\necho \"===== GPU Summary =====\"\nnvidia-smi \\\n  --query-gpu=index,name,memory.total,memory.used,memory.free,utilization.gpu \\\n  --format=csv 2>\/dev\/null || true\n\necho\necho \"===== Scheduler =====\"\ncommand -v srun || true\ncommand -v sbatch || true\n\necho\necho \"===== Conda =====\"\ncommand -v conda || true\nconda env list 2>\/dev\/null || true\n\necho\necho \"===== Current Python =====\"\ncommand -v python || true\npython --version 2>\/dev\/null || true<\/code><\/pre>\n\n\n\n
            \u8d4b\u6743\u5e76\u8fd0\u884c\uff1a<\/p>\n\n\n\n
            chmod +x \/app\/hd\/data01\/username\/projects\/check_server.sh\n\/app\/hd\/data01\/username\/projects\/check_server.sh<\/code><\/pre>\n\n\n\n
            \n\n\n\n
            \u4e8c\u5341\u3001\u5b8c\u6574\u590d\u76d8<\/h1>\n\n\n\n
            \u4eca\u5929\u5b8c\u6210\u7684\u5173\u952e\u6b65\u9aa4\u53ef\u4ee5\u6982\u62ec\u4e3a\uff1a<\/p>\n\n\n\n
            1. \u521b\u5efa\u72ec\u7acb Linux \u7528\u6237\n2. \u914d\u7f6e sudo \u548c\u4e2a\u4eba Home\n3. \u5728\u65e0 Python \u73af\u5883\u4e0b\u5b89\u88c5 Miniconda\n4. \u5904\u7406 Conda \u521d\u59cb\u5316\u548c ToS\n5. \u53d1\u73b0\u6839\u5206\u533a\u5df2\u6ee1\n6. \u627e\u5230\u5927\u5bb9\u91cf\u6570\u636e\u76d8\n7. \u5c06 Conda \u73af\u5883\u3001\u7f13\u5b58\u3001\u4e34\u65f6\u6587\u4ef6\u548c\u6a21\u578b\u8fc1\u79fb\u5230\u6570\u636e\u76d8\n8. \u5b89\u88c5 qwen-asr[vllm]\n9. \u4e0b\u8f7d Qwen3-ASR \u6a21\u578b\n10. \u9a8c\u8bc1 PyTorch \u548c CUDA\n11. \u542f\u52a8 vLLM \u6d41\u5f0f ASR Demo\n12. \u67e5\u770b\u5b9e\u9645\u5360\u7528\u7684\u7269\u7406 GPU\n13. \u4f7f\u7528 CUDA_VISIBLE_DEVICES \u907f\u5f00\u5176\u4ed6\u7528\u6237\u5b9e\u9a8c\n14. \u901a\u8fc7 Windows SSH \u96a7\u9053\u8bbf\u95ee\u670d\u52a1\n15. \u89e3\u51b3 Windows \u672c\u5730\u7aef\u53e3 Permission denied<\/code><\/pre>\n\n\n\n
            \u6700\u503c\u5f97\u8bb0\u4f4f\u7684\u7ecf\u9a8c\u662f\uff1a<\/p>\n\n\n\n
            \n
            \u5148\u76d8\u70b9\uff0c\u518d\u5b89\u88c5\uff1b\u5148\u89c4\u5212\u78c1\u76d8\uff0c\u518d\u4e0b\u8f7d\uff1b\u5148\u786e\u8ba4 GPU\uff0c\u518d\u542f\u52a8\uff1b\u6d4b\u8bd5\u670d\u52a1\u53ea\u76d1\u542c\u672c\u673a\uff0c\u901a\u8fc7 SSH \u96a7\u9053\u8bbf\u95ee\u3002<\/strong><\/p>\n<\/blockquote>\n\n\n\n
            \u8fdb\u5165\u7532\u65b9\u73af\u5883\u540e\uff0c\u90e8\u7f72\u6210\u529f\u5e76\u4e0d\u53ea\u662f\u201c\u6a21\u578b\u80fd\u8dd1\u8d77\u6765\u201d\uff0c\u8fd8\u5fc5\u987b\u540c\u65f6\u8003\u8651\uff1a<\/p>\n\n\n\n
              \n
            • \u6743\u9650\u9694\u79bb\uff1b<\/li>\n\n\n\n
            • \u78c1\u76d8\u89c4\u5212\uff1b<\/li>\n\n\n\n
            • GPU \u8c03\u5ea6\uff1b<\/li>\n\n\n\n
            • \u7f51\u7edc\u8fb9\u754c\uff1b<\/li>\n\n\n\n
            • \u8f6f\u4ef6\u8bb8\u53ef\uff1b<\/li>\n\n\n\n
            • \u5b89\u5168\u5ba1\u8ba1\uff1b<\/li>\n\n\n\n
            • \u65e5\u5fd7\u7ba1\u7406\uff1b<\/li>\n\n\n\n
            • \u670d\u52a1\u6258\u7ba1\uff1b<\/li>\n\n\n\n
            • \u6545\u969c\u6062\u590d\uff1b<\/li>\n\n\n\n
            • \u540e\u7eed\u8fd0\u7ef4\u3002<\/li>\n<\/ul>\n\n\n\n
              \n\n\n\n
              \u9644\u5f55 A\uff1a\u672c\u6b21\u6700\u5e38\u7528\u547d\u4ee4\u901f\u67e5<\/h1>\n\n\n\n
              \u6fc0\u6d3b\u73af\u5883<\/h2>\n\n\n\n
              conda activate \/app\/hd\/data01\/username\/conda_envs\/qwen3-asr<\/code><\/pre>\n\n\n\n
              \u67e5\u770b GPU<\/h2>\n\n\n\n
              nvidia-smi\nnvidia-smi pmon -c 1<\/code><\/pre>\n\n\n\n
              \u6307\u5b9a GPU \u542f\u52a8<\/h2>\n\n\n\n
              CUDA_VISIBLE_DEVICES=5 \\\nqwen-asr-demo-streaming \\\n  --asr-model-path \/app\/hd\/data01\/username\/models\/Qwen3-ASR-0.6B \\\n  --gpu-memory-utilization 0.60 \\\n  --host 127.0.0.1 \\\n  --port 10095<\/code><\/pre>\n\n\n\n
              Windows SSH \u96a7\u9053<\/h2>\n\n\n\n
              ssh -N `\n  -L 127.0.0.1:18095:127.0.0.1:10095 `\n  username@\u670d\u52a1\u5668\u5730\u5740<\/code><\/pre>\n\n\n\n
              \u6d4f\u89c8\u5668\u8bbf\u95ee<\/h2>\n\n\n\n
              http://127.0.0.1:18095<\/code><\/pre>\n\n\n\n
              \u67e5\u770b\u76ee\u5f55\u5360\u7528<\/h2>\n\n\n\n
              du -h --max-depth=1 \/app\/hd\/data01\/username | sort -h<\/code><\/pre>\n\n\n\n
              \u67e5\u770b\u6839\u5206\u533a<\/h2>\n\n\n\n
              df -h \/<\/code><\/pre>\n\n\n\n
              \u505c\u6b62\u670d\u52a1<\/h2>\n\n\n\n
              Ctrl + C<\/code><\/pre>\n\n\n\n
              \n\n\n\n
              \u9644\u5f55 B\uff1a\u7532\u65b9\u90e8\u7f72\u8bb0\u5f55\u6a21\u677f<\/h1>\n\n\n\n
              \u9879\u76ee\u540d\u79f0\uff1a\n\u5ba2\u6237\u540d\u79f0\uff1a\n\u90e8\u7f72\u65e5\u671f\uff1a\n\u90e8\u7f72\u4eba\u5458\uff1a\n\n\u670d\u52a1\u5668\u4e3b\u673a\u540d\uff1a\n\u64cd\u4f5c\u7cfb\u7edf\uff1a\nCPU \u67b6\u6784\uff1a\n\u5185\u5b58\uff1a\nGPU \u578b\u53f7\u4e0e\u6570\u91cf\uff1a\nNVIDIA \u9a71\u52a8\u7248\u672c\uff1a\nCUDA \u53ef\u89c1\u7248\u672c\uff1a\n\u662f\u5426\u4f7f\u7528\u8c03\u5ea6\u5668\uff1a\n\n\u8fd0\u884c\u8d26\u53f7\uff1a\n\u73af\u5883\u76ee\u5f55\uff1a\n\u6a21\u578b\u76ee\u5f55\uff1a\n\u7f13\u5b58\u76ee\u5f55\uff1a\n\u65e5\u5fd7\u76ee\u5f55\uff1a\n\u670d\u52a1\u7aef\u53e3\uff1a\n\u76d1\u542c\u5730\u5740\uff1a\n\u6307\u5b9a GPU\uff1a\n\u6a21\u578b\u7248\u672c\uff1a\nPython \u7248\u672c\uff1a\nPyTorch \u7248\u672c\uff1a\nvLLM \u7248\u672c\uff1a\n\n\u5b89\u88c5\u65b9\u5f0f\uff1a\u5728\u7ebf \/ \u79bb\u7ebf\n\u7f51\u7edc\u4ee3\u7406\uff1a\n\u955c\u50cf\u6e90\uff1a\n\u9632\u706b\u5899\u7b56\u7565\uff1a\n\u8bbf\u95ee\u65b9\u5f0f\uff1aSSH \u96a7\u9053 \/ \u53cd\u5411\u4ee3\u7406 \/ \u5185\u7f51\u76f4\u8fde\n\n\u542f\u52a8\u547d\u4ee4\uff1a\n\u505c\u6b62\u547d\u4ee4\uff1a\n\u5065\u5eb7\u68c0\u67e5\u547d\u4ee4\uff1a\n\u65e5\u5fd7\u67e5\u770b\u547d\u4ee4\uff1a\n\u56de\u6eda\u65b9\u6848\uff1a\n\n\u6d4b\u8bd5\u97f3\u9891\uff1a\n\u8bc6\u522b\u7ed3\u679c\uff1a\n\u9996\u5b57\u5ef6\u8fdf\uff1a\n\u6700\u7ec8\u7ed3\u679c\u5ef6\u8fdf\uff1a\n\u663e\u5b58\u5360\u7528\uff1a\nGPU \u5229\u7528\u7387\uff1a\n\u5df2\u77e5\u95ee\u9898\uff1a\n\u540e\u7eed\u4e8b\u9879\uff1a<\/code><\/pre>\n\n\n\n
              <\/p>\n","protected":false},"excerpt":{"rendered":"
              \u672c\u6587\u8bb0\u5f55\u4e86\u4e00\u6b21\u4ece\u201c\u670d\u52a1\u5668\u4e0a\u51e0\u4e4e\u6ca1\u6709\u4e2a\u4eba\u5f00\u53d1\u73af\u5883\u201d\u5f00\u59cb\uff0c\u5b8c\u6210 Linux \u7528\u6237\u9694\u79bb\u3001Miniconda \u5b89\u88c5\u3001\u78c1 […]<\/p>\n","protected":false},"author":1,"featured_media":816,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[57,1],"tags":[70,68,71,69],"class_list":["post-812","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","category-uncategorized","tag-asr","tag-linux","tag-qwen","tag-69"],"jetpack_sharing_enabled":true,"jetpack_featured_media_url":"https:\/\/blog.heartwarming.online\/wp-content\/uploads\/2026\/07\/pexels-photo-11034131.jpeg","_links":{"self":[{"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/posts\/812","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/comments?post=812"}],"version-history":[{"count":2,"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/posts\/812\/revisions"}],"predecessor-version":[{"id":815,"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/posts\/812\/revisions\/815"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/media\/816"}],"wp:attachment":[{"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/media?parent=812"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/categories?post=812"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.heartwarming.online\/index.php\/wp-json\/wp\/v2\/tags?post=812"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}