Merge pull request #2082 from opendatalab/dev

docs(user_guide): update installation guide and CUDA support

Merge pull request #2082 from opendatalab/dev
docs(user_guide): update installation guide and CUDA support
01054426 · Xiaomeng Zhao · GitHub · 579057dd · 5c46c791 · 01054426
Unverified Commit 01054426 authored Apr 03, 2025 by Xiaomeng Zhao Committed by GitHub Apr 03, 2025
4 changed files
--- a/next_docs/en/user_guide/install/boost_with_cuda.rst
+++ b/next_docs/en/user_guide/install/boost_with_cuda.rst
@@ -28,12 +28,12 @@ NVIDIA drivers are already installed, and you can skip Step 2.
 .. note::
-   ``CUDA Version`` should be >= 12.1, If the displayed version number is less than 12.1, please upgrade the driver.
+   ``CUDA Version`` should be >= 12.4, If the displayed version number is less than 12.4, please upgrade the driver.
 .. code:: text
   +---------------------------------------------------------------------------------------+
-   | NVIDIA-SMI 537.34                 Driver Version: 537.34       CUDA Version: 12.2     |
+   | NVIDIA-SMI 570.133.07             Driver Version: 572.83         CUDA Version: 12.8   |
   |-----------------------------------------+----------------------+----------------------+
   | GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |
   | Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
@@ -52,7 +52,7 @@ If no driver is installed, use the following command:
 .. code:: sh
   sudo apt-get update
-   sudo apt-get install nvidia-driver-545
+   sudo apt-get install nvidia-driver-570-server
 Install the proprietary driver and restart your computer after
 installation.
@@ -80,15 +80,15 @@ Specify Python version 3.10.
 .. code:: sh
-   conda create -n MinerU python=3.10
+    conda create -n mineru 'python<3.13' -y
-   conda activate MinerU
+    conda activate mineru
 5. Install Applications
 ~~~~~~~~~~~~~~~~~~~~~~~
 .. code:: sh
-   pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
+   pip install -U magic-pdf[full]
 .. admonition:: Important
    :class: tip
@@ -99,7 +99,7 @@ Specify Python version 3.10.
   magic-pdf --version
-If the version number is less than 0.7.0, please report the issue.
+If the version number is less than 1.3.0, please report the issue.
 6. Download Models
 ~~~~~~~~~~~~~~~~~~
@@ -126,7 +126,7 @@ Download a sample file from the repository and test it.
 .. code:: sh
-   wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf
+   wget https://github.com/opendatalab/MinerU/raw/master/demo/pdfs/small_ocr.pdf
   magic-pdf -p small_ocr.pdf -o ./output
 9. Test CUDA Acceleration
@@ -150,23 +150,6 @@ to test CUDA acceleration:
      magic-pdf -p small_ocr.pdf -o ./output
-10. Enable CUDA Acceleration for OCR
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-1. Download ``paddlepaddle-gpu``. Installation will automatically enable
-   OCR acceleration.
-   .. code:: sh
-      python -m pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/
-2. Test OCR acceleration with the following command:
-   .. code:: sh
-      magic-pdf -p small_ocr.pdf -o ./output
 .. _windows_10_or_11_section:
@@ -176,11 +159,12 @@ Windows 10/11
 1. Install CUDA and cuDNN
 ~~~~~~~~~~~~~~~~~~~~~~~~~
-Required versions: CUDA 11.8 + cuDNN 8.7.0
+You need to install a CUDA version that is compatible with torch's requirements. Currently, torch supports CUDA 11.8/12.4/12.6.
+- CUDA 11.8 https://developer.nvidia.com/cuda-11-8-0-download-archive
+- CUDA 12.4 https://developer.nvidia.com/cuda-12-4-0-download-archive
+- CUDA 12.6 https://developer.nvidia.com/cuda-12-6-0-download-archive
-  CUDA 11.8: https://developer.nvidia.com/cuda-11-8-0-download-archive
-  cuDNN v8.7.0 (November 28th, 2022), for CUDA 11.x:
-   https://developer.nvidia.com/rdp/cudnn-archive
 2. Install Anaconda
 ~~~~~~~~~~~~~~~~~~~
@@ -192,19 +176,17 @@ Download link: https://repo.anaconda.com/archive/Anaconda3-2024.06-1-Windows-x86
 3. Create an Environment Using Conda
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-Python version must be 3.10.
 ::
-   conda create -n MinerU python=3.10
+    conda create -n mineru 'python<3.13' -y
-   conda activate MinerU
+    conda activate mineru
 4. Install Applications
 ~~~~~~~~~~~~~~~~~~~~~~~
 ::
-   pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
+   pip install -U magic-pdf[full]
 .. admonition:: Important
    :class: tip
@@ -215,7 +197,7 @@ Python version must be 3.10.
      magic-pdf --version
-    If the version number is less than 0.7.0, please report it in the issues section.
+    If the version number is less than 1.3.0, please report it in the issues section.
 5. Download Models
 ~~~~~~~~~~~~~~~~~~
@@ -242,7 +224,7 @@ Download a sample file from the repository and test it.
 .. code:: powershell
-     wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf -O small_ocr.pdf
+     wget https://github.com/opendatalab/MinerU/raw/master/demo/pdfs/small_ocr.pdf -O small_ocr.pdf
     magic-pdf -p small_ocr.pdf -o ./output
 8. Test CUDA Acceleration
@@ -251,23 +233,12 @@ Download a sample file from the repository and test it.
 If your graphics card has at least 8GB of VRAM, follow these steps to
 test CUDA-accelerated parsing performance.
-1. **Overwrite the installation of torch and torchvision** supporting CUDA.
+1. **Overwrite the installation of torch and torchvision** supporting CUDA.(Please select the appropriate index-url based on your CUDA version. For more details, refer to the [PyTorch official website](https://pytorch.org/get-started/locally/).)
 .. code:: sh
-   pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 --index-url https://download.pytorch.org/whl/cu118
+   pip install --force-reinstall torch==2.6.0 torchvision==0.21.1 "numpy<2.0.0" --index-url https://download.pytorch.org/whl/cu124
-.. admonition:: Important
-    :class: tip
-    ❗️Ensure the following versions are specified in the command:
-    .. code:: sh
-         torch==2.3.1 torchvision==0.18.1
-    These are the highest versions we support. Installing higher versions without specifying them will cause the program to fail.
 2. **Modify the value of ``"device-mode"``** in the ``magic-pdf.json``
   configuration file located in your user directory.
@@ -283,19 +254,3 @@ test CUDA-accelerated parsing performance.
   ::
      magic-pdf -p small_ocr.pdf -o ./output
-9. Enable CUDA Acceleration for OCR
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-1. **Download paddlepaddle-gpu**, which will automatically enable OCR
-   acceleration upon installation.
-   ::
-      pip install paddlepaddle-gpu==2.6.1
-2. **Run the following command to test OCR acceleration**:
-   ::
-      magic-pdf -p small_ocr.pdf -o ./output
--- a/next_docs/en/user_guide/install/install.rst
+++ b/next_docs/en/user_guide/install/install.rst
@@ -37,53 +37,57 @@ Also you can try `online demo <https://www.modelscope.cn/studios/OpenDataLab/Min
        }
    </style>
    <table>
-        <tr>
+    <tr>
-            <td colspan="3" rowspan="2">Operating System</td>
+        <td colspan="3" rowspan="2">Operating System</td>
-        </tr>
+    </tr>
-        <tr>
+    <tr>
-            <td>Ubuntu 22.04 LTS</td>
+        <td>Linux after 2019</td>
-            <td>Windows 10 / 11</td>
+        <td>Windows 10 / 11</td>
-            <td>macOS 11+</td>
+        <td>macOS 11+</td>
-        </tr>
+    </tr>
-        <tr>
+    <tr>
-            <td colspan="3">CPU</td>
+        <td colspan="3">CPU</td>
-            <td>x86_64(unsupported ARM Linux)</td>
+        <td>x86_64 / arm64</td>
-            <td>x86_64(unsupported ARM Windows)</td>
+        <td>x86_64(unsupported ARM Windows)</td>
-            <td>x86_64 / arm64</td>
+        <td>x86_64 / arm64</td>
-        </tr>
+    </tr>
-        <tr>
+    <tr>
-            <td colspan="3">Memory</td>
+        <td colspan="3">Memory Requirements</td>
-            <td colspan="3">16GB or more, recommended 32GB+</td>
+        <td colspan="3">16GB or more, recommended 32GB+</td>
-        </tr>
+    </tr>
-        <tr>
+    <tr>
-            <td colspan="3">Python Version</td>
+        <td colspan="3">Storage Requirements</td>
-            <td colspan="3">3.10(Please make sure to create a Python 3.10 virtual environment using conda)</td>
+        <td colspan="3">20GB or more, with a preference for SSD</td>
-        </tr>
+    </tr>
-        <tr>
+    <tr>
-            <td colspan="3">Nvidia Driver Version</td>
+        <td colspan="3">Python Version</td>
-            <td>latest (Proprietary Driver)</td>
+        <td colspan="3">3.10~3.12</td>
-            <td>latest</td>
+    </tr>
-            <td>None</td>
+    <tr>
-        </tr>
+        <td colspan="3">Nvidia Driver Version</td>
-        <tr>
+        <td>latest (Proprietary Driver)</td>
-            <td colspan="3">CUDA Environment</td>
+        <td>latest</td>
-            <td>Automatic installation [12.1 (pytorch) + 11.8 (paddle)]</td>
+        <td>None</td>
-            <td>11.8 (manual installation) + cuDNN v8.7.0 (manual installation)</td>
+    </tr>
-            <td>None</td>
+    <tr>
-        </tr>
+        <td colspan="3">CUDA Environment</td>
-        <tr>
+        <td>11.8/12.4/12.6</td>
-            <td rowspan="2">GPU Hardware Support List</td>
+        <td>11.8/12.4/12.6</td>
-            <td colspan="2">Minimum Requirement 8G+ VRAM</td>
+        <td>None</td>
-            <td colspan="2">3060ti/3070/4060<br>
+    </tr>
-            8G VRAM enables layout, formula recognition acceleration and OCR acceleration</td>
+    <tr>
-            <td rowspan="2">None</td>
+        <td colspan="3">CANN Environment(NPU support)</td>
-        </tr>
+        <td>8.0+(Ascend 910b)</td>
-        <tr>
+        <td>None</td>
-            <td colspan="2">Recommended Configuration 10G+ VRAM</td>
+        <td>None</td>
-            <td colspan="2">3080/3080ti/3090/3090ti/4070/4070ti/4070tisuper/4080/4090<br>
+    </tr>
-            10G VRAM or more can enable layout, formula recognition, OCR acceleration and table recognition acceleration simultaneously
+    <tr>
-            </td>
+        <td rowspan="2">GPU/MPS Hardware Support List</td>
-        </tr>
+        <td colspan="2">GPU VRAM 6GB or more</td>
+        <td colspan="2">All GPUs with Tensor Cores produced from Volta(2017) onwards.<br>
+        More than 6GB VRAM </td>
+        <td rowspan="2">apple slicon</td>
+    </tr>
    </table>
@@ -93,9 +97,9 @@ Create an environment
 .. code-block:: shell
-    conda create -n MinerU python=3.10
+    conda create -n mineru 'python<3.13' -y
-    conda activate MinerU
+    conda activate mineru
-    pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
+    pip install -U "magic-pdf[full]"
 Download model weight files

--- a/next_docs/zh_cn/user_guide/install/boost_with_cuda.rst
+++ b/next_docs/zh_cn/user_guide/install/boost_with_cuda.rst
@@ -10,7 +10,7 @@
 .. admonition:: Important
    :class: tip
-    Docker 需要至少 16GB 显存的 GPU，并且所有加速功能默认启用。
+    Docker 需要至少 6GB 显存的 GPU，并且所有加速功能默认启用。
    在运行此 Docker 容器之前，您可以使用以下命令检查您的设备是否支持 Docker 上的 CUDA 加速。
@@ -20,10 +20,10 @@
 .. code:: sh
-    wget https://github.com/opendatalab/MinerU/raw/master/Dockerfile
+      wget https://gcore.jsdelivr.net/gh/opendatalab/MinerU@master/docker/china/Dockerfile -O Dockerfile
-    docker build -t mineru:latest .
+      docker build -t mineru:latest .
-    docker run --rm -it --gpus=all mineru:latest /bin/bash
+      docker run -it --name mineru --gpus=all mineru:latest /bin/bash -c "echo 'source /opt/mineru_venv/bin/activate' >> ~/.bashrc && exec bash"
-    magic-pdf --help
+      magic-pdf --help
 .. _ubuntu_22_04_lts_section:
@@ -42,12 +42,12 @@ Ubuntu 22.04 LTS
 .. admonition:: Important
    :class: tip
-    ``CUDA Version`` 显示的版本号应 >=12.1，如显示的版本号小于12.1，请升级驱动
+    ``CUDA Version`` 显示的版本号应 >= 12.4，如显示的版本号小于12.4，请升级驱动
 .. code:: text
   +---------------------------------------------------------------------------------------+
-   | NVIDIA-SMI 537.34                 Driver Version: 537.34       CUDA Version: 12.2     |
+   | NVIDIA-SMI 570.133.07             Driver Version: 572.83         CUDA Version: 12.8   |
   |-----------------------------------------+----------------------+----------------------+
   | GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |
   | Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
@@ -66,7 +66,7 @@ Ubuntu 22.04 LTS
 .. code:: bash
   sudo apt-get update
-   sudo apt-get install nvidia-driver-545
+   sudo apt-get install nvidia-driver-570-server
 安装专有驱动，安装完成后，重启电脑
@@ -89,19 +89,17 @@ Ubuntu 22.04 LTS
 4. 使用 conda 创建环境
 ---------------------
-需指定 python 版本为3.10
 .. code:: bash
-   conda create -n MinerU python=3.10
+   conda create -n mineru 'python<3.13' -y
-   conda activate MinerU
+   conda activate mineru
 5. 安装应用
 -----------
 .. code:: bash
-   pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i https://mirrors.aliyun.com/pypi/simple
+   pip install -U magic-pdf[full] -i https://mirrors.aliyun.com/pypi/simple
 .. admonition:: Important
    :class: tip
@@ -112,7 +110,7 @@ Ubuntu 22.04 LTS
       magic-pdf --version
-    如果版本号小于0.7.0，请到issue中向我们反馈
+    如果版本号小于1.3.0，请到issue中向我们反馈
 6. 下载模型
 -----------
@@ -136,7 +134,7 @@ Ubuntu 22.04 LTS
 .. code:: bash
-   wget https://gcore.jsdelivr.net/gh/opendatalab/MinerU@master/demo/small_ocr.pdf
+   wget https://gcore.jsdelivr.net/gh/opendatalab/MinerU@master/demo/pdfs/small_ocr.pdf
   magic-pdf -p small_ocr.pdf -o ./output
 9. 测试CUDA加速
@@ -163,27 +161,8 @@ Ubuntu 22.04 LTS
 .. admonition:: Tip
    :class: tip
-    CUDA 加速是否生效可以根据 log 中输出的各个阶段 cost 耗时来简单判断，通常情况下， ``layout detection cost`` 和 ``mfr time`` 应提速10倍以上。
+    CUDA 加速是否生效可以根据 log 中输出的各个阶段的耗时来简单判断，通常情况下，cuda应比cpu更快。
-10. 为 ocr 开启 cuda 加速
---------------------
-**1.下载paddlepaddle-gpu, 安装完成后会自动开启ocr加速**
-.. code:: bash
-   python -m pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/
-**2.运行以下命令测试ocr加速效果**
-.. code:: bash
-   magic-pdf -p small_ocr.pdf -o ./output
-.. admonition:: Tip
-    :class: tip
-    CUDA 加速是否生效可以根据 log 中输出的各个阶段 cost 耗时来简单判断，通常情况下， ``ocr cost`` 应提速10倍以上。
 .. _windows_10_or_11_section:
@@ -194,10 +173,12 @@ Windows 10/11
 1. 安装 cuda 和 cuDNN
 ------------------
-需要安装的版本 CUDA 11.8 + cuDNN 8.7.0
+需要安装符合torch要求的cuda版本，torch目前支持11.8/12.4/12.6
+- CUDA 11.8 https://developer.nvidia.com/cuda-11-8-0-download-archive
+- CUDA 12.4 https://developer.nvidia.com/cuda-12-4-0-download-archive
+- CUDA 12.6 https://developer.nvidia.com/cuda-12-6-0-download-archive
-  CUDA 11.8 https://developer.nvidia.com/cuda-11-8-0-download-archive
-  cuDNN v8.7.0 (November 28th, 2022), for CUDA 11.x https://developer.nvidia.com/rdp/cudnn-archive
 2. 安装 anaconda
 ---------------
@@ -209,19 +190,17 @@ Windows 10/11
 3. 使用 conda 创建环境
 ---------------------
-需指定python版本为3.10
 .. code:: bash
-   conda create -n MinerU python=3.10
+    conda create -n mineru 'python<3.13' -y
-   conda activate MinerU
+    conda activate mineru
 4. 安装应用
 -----------
 .. code:: bash
-   pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i https://mirrors.aliyun.com/pypi/simple
+   pip install -U magic-pdf[full] -i https://mirrors.aliyun.com/pypi/simple
 .. admonition:: Important
    :class: tip
@@ -232,7 +211,7 @@ Windows 10/11
      magic-pdf --version
-    如果版本号小于0.7.0，请到issue中向我们反馈
+    如果版本号小于1.3.0，请到issue中向我们反馈
 5. 下载模型
 -----------
@@ -256,7 +235,7 @@ Windows 10/11
 .. code:: powershell
-    wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf -O small_ocr.pdf
+    wget https://github.com/opendatalab/MinerU/raw/master/demo/pdfs/small_ocr.pdf -O small_ocr.pdf
    magic-pdf -p small_ocr.pdf -o ./output
 8. 测试 CUDA 加速
@@ -264,22 +243,13 @@ Windows 10/11
 如果您的显卡显存大于等于 **8GB**，可以进行以下流程，测试 CUDA 解析加速效果
-**1.覆盖安装支持cuda的torch和torchvision**
+**1.覆盖安装支持cuda的torch和torchvision**(请根据cuda版本选择合适的index-url，具体可参考[torch官网](https://pytorch.org/get-started/locally/))
-.. code:: bash
-   pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 --index-url https://download.pytorch.org/whl/cu118
-.. admonition:: Important
-    :class: tip
-    务必在命令中指定以下版本
+.. code:: bash
-    .. code:: bash
-      torch==2.3.1 torchvision==0.18.1
+   pip install --force-reinstall torch==2.6.0 torchvision==0.21.1 "numpy<2.0.0" --index-url https://download.pytorch.org/whl/cu124
-    这是我们支持的最高版本，如果不指定版本会自动安装更高版本导致程序无法运行
 **2.修改【用户目录】中配置文件magic-pdf.json中”device-mode”的值**
@@ -298,24 +268,5 @@ Windows 10/11
 .. admonition:: Tip
    :class: tip
-    CUDA 加速是否生效可以根据 log 中输出的各个阶段的耗时来简单判断，通常情况下， ``layout detection time`` 和 ``mfr time`` 应提速10倍以上。
+    CUDA 加速是否生效可以根据 log 中输出的各个阶段的耗时来简单判断，通常情况下， cuda会比cpu更快。
-9. 为 ocr 开启 cuda 加速
--------------------
-**1.下载paddlepaddle-gpu, 安装完成后会自动开启ocr加速**
-.. code:: bash
-   pip install paddlepaddle-gpu==2.6.1
-**2.运行以下命令测试ocr加速效果**
-.. code:: bash
-   magic-pdf -p small_ocr.pdf -o ./output
-.. admonition:: Tip
-    :class: tip
-    CUDA 加速是否生效可以根据 log 中输出的各个阶段 cost 耗时来简单判断，通常情况下， ``ocr time`` 应提速10倍以上。
--- a/next_docs/zh_cn/user_guide/install/install.rst
+++ b/next_docs/zh_cn/user_guide/install/install.rst
@@ -24,53 +24,58 @@
        }
    </style>
    <table>
-        <tr>
+    <tr>
-            <td colspan="3" rowspan="2">操作系统</td>
+        <td colspan="3" rowspan="2">操作系统</td>
-        </tr>
+    </tr>
-        <tr>
+    <tr>
-            <td>Ubuntu 22.04 LTS</td>
+        <td>Linux after 2019</td>
-            <td>Windows 10 / 11</td>
+        <td>Windows 10 / 11</td>
-            <td>macOS 11+</td>
+        <td>macOS 11+</td>
-        </tr>
+    </tr>
-        <tr>
+    <tr>
-            <td colspan="3">CPU</td>
+        <td colspan="3">CPU</td>
-            <td>x86_64(暂不支持ARM Linux)</td>
+        <td>x86_64 / arm64</td>
-            <td>x86_64(暂不支持ARM Windows)</td>
+        <td>x86_64(暂不支持ARM Windows)</td>
-            <td>x86_64 / arm64</td>
+        <td>x86_64 / arm64</td>
-        </tr>
+    </tr>
-        <tr>
+    <tr>
-            <td colspan="3">内存</td>
+        <td colspan="3">内存</td>
-            <td colspan="3">大于等于16GB，推荐32G以上</td>
+        <td colspan="3">大于等于16GB，推荐32G以上</td>
-        </tr>
+    </tr>
-        <tr>
+    <tr>
-            <td colspan="3">python版本</td>
+        <td colspan="3">存储空间</td>
-            <td colspan="3">3.10 (请务必通过conda创建3.10虚拟环境)</td>
+        <td colspan="3">大于等于20GB，推荐使用SSD以获得最佳性能</td>
-        </tr>
+    </tr>
-        <tr>
+    <tr>
-            <td colspan="3">Nvidia Driver 版本</td>
+        <td colspan="3">python版本</td>
-            <td>latest(专有驱动)</td>
+        <td colspan="3">>=3.9,<=3.12</td>
-            <td>latest</td>
+    </tr>
-            <td>None</td>
+    <tr>
-        </tr>
+        <td colspan="3">Nvidia Driver 版本</td>
-        <tr>
+        <td>latest(专有驱动)</td>
-            <td colspan="3">CUDA环境</td>
+        <td>latest</td>
-            <td>自动安装[12.1(pytorch)+11.8(paddle)]</td>
+        <td>None</td>
-            <td>11.8(手动安装)+cuDNN v8.7.0(手动安装)</td>
+    </tr>
-            <td>None</td>
+    <tr>
-        </tr>
+        <td colspan="3">CUDA环境</td>
-        <tr>
+        <td>11.8/12.4/12.6</td>
-            <td rowspan="2">GPU硬件支持列表</td>
+        <td>11.8/12.4/12.6</td>
-            <td colspan="2">最低要求 8G+显存</td>
+        <td>None</td>
-            <td colspan="2">3060ti/3070/4060<br>
+    </tr>
-            8G显存可开启layout、公式识别和ocr加速</td>
+    <tr>
-            <td rowspan="2">None</td>
+        <td colspan="3">CANN环境(NPU支持)</td>
-        </tr>
+        <td>8.0+(Ascend 910b)</td>
-        <tr>
+        <td>None</td>
-            <td colspan="2">推荐配置 10G+显存</td>
+        <td>None</td>
-            <td colspan="2">3080/3080ti/3090/3090ti/4070/4070ti/4070tisuper/4080/4090<br>
+    </tr>
-            10G显存及以上可以同时开启layout、公式识别和ocr加速和表格识别加速<br>
+    <tr>
-            </td>
+        <td rowspan="2">GPU/MPS 硬件支持列表</td>
-        </tr>
+        <td colspan="2">显存6G以上</td>
+        <td colspan="2">
+        Volta(2017)及之后生产的全部带Tensor Core的GPU <br>
+        6G显存及以上</td>
+        <td rowspan="2">apple slicon</td>
+    </tr>
    </table>
@@ -79,9 +84,9 @@
 .. code-block:: shell
-    conda create -n MinerU python=3.10
+    conda create -n mineru 'python<3.13' -y
-    conda activate MinerU
+    conda activate mineru
-    pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i https://mirrors.aliyun.com/pypi/simple
+    pip install -U "magic-pdf[full]" -i https://mirrors.aliyun.com/pypi/simple
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