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fix: update advanced_cli_parameters.md to clarify parameter passing for vllm and lmdeploy

myhloli 1 week ago
parent
commit
c5385af754
2 changed files with 14 additions and 12 deletions
  1. 7 6
      docs/en/usage/advanced_cli_parameters.md
  2. 7 6
      docs/zh/usage/advanced_cli_parameters.md

+ 7 - 6
docs/en/usage/advanced_cli_parameters.md

@@ -1,8 +1,8 @@
 # Advanced Command Line Parameters
 
-## vllm Acceleration Parameter Optimization
+## Pass-through of inference engine parameters
 
-### Performance Optimization Parameters
+### vllm Acceleration Parameter Optimization
 > [!TIP]
 > If you can already use vllm normally for accelerated VLM model inference but still want to further improve inference speed, you can try the following parameters:
 > 
@@ -10,8 +10,9 @@
 
 ### Parameter Passing Instructions
 > [!TIP]
-> - All officially supported vllm parameters can be passed to MinerU through command line arguments, including the following commands: `mineru`, `mineru-vllm-server`, `mineru-gradio`, `mineru-api`
+> - All officially supported vllm/lmdeploy parameters can be passed to MinerU through command line arguments, including the following commands: `mineru`, `mineru-openai-server`, `mineru-gradio`, `mineru-api`
 > - If you want to learn more about `vllm` parameter usage, please refer to the [vllm official documentation](https://docs.vllm.ai/en/latest/cli/serve.html)
+> - If you want to learn more about `lmdeploy` parameter usage, please refer to the [lmdeploy official documentation](https://lmdeploy.readthedocs.io/en/latest/llm/api_server.html)
 
 ## GPU Device Selection and Configuration
 
@@ -21,7 +22,7 @@
 >   ```bash
 >   CUDA_VISIBLE_DEVICES=1 mineru -p <input_path> -o <output_path>
 >   ```
-> - This specification method is effective for all command line calls, including `mineru`, `mineru-vllm-server`, `mineru-gradio`, and `mineru-api`, and applies to both `pipeline` and `vlm` backends.
+> - This specification method is effective for all command line calls, including `mineru`, `mineru-openai-server`, `mineru-gradio`, and `mineru-api`, and applies to both `pipeline` and `vlm` backends.
 
 ### Common Device Configuration Examples
 > [!TIP]
@@ -38,9 +39,9 @@
 > [!TIP]
 > Here are some possible usage scenarios:
 > 
-> - If you have multiple graphics cards and need to specify cards 0 and 1, using multi-card parallelism to start `vllm-server`, you can use the following command:
+> - If you have multiple graphics cards and need to specify cards 0 and 1, using multi-card parallelism to start `openai-server`, you can use the following command:
 >   ```bash
->   CUDA_VISIBLE_DEVICES=0,1 mineru-vllm-server --port 30000 --data-parallel-size 2
+>   CUDA_VISIBLE_DEVICES=0,1 mineru-openai-server --engine vllm --port 30000 --data-parallel-size 2
 >   ```
 >       
 > - If you have multiple graphics cards and need to start two `fastapi` services on cards 0 and 1, listening on different ports respectively, you can use the following commands:

+ 7 - 6
docs/zh/usage/advanced_cli_parameters.md

@@ -1,8 +1,8 @@
 # 命令行参数进阶
 
-## vllm 加速参数优化
+## 推理引擎参数透传
 
-### 性能优化参数
+### vllm 加速参数优化
 > [!TIP]
 > 如果您已经可以正常使用vllm对vlm模型进行加速推理,但仍然希望进一步提升推理速度,可以尝试以下参数:
 > 
@@ -10,8 +10,9 @@
 
 ### 参数传递说明
 > [!TIP]
-> - 所有vllm官方支持的参数都可用通过命令行参数传递给 MinerU,包括以下命令:`mineru`、`mineru-vllm-server`、`mineru-gradio`、`mineru-api`
+> - 所有vllm/lmdeploy官方支持的参数都可用通过命令行参数传递给 MinerU,包括以下命令:`mineru`、`mineru-openai-server`、`mineru-gradio`、`mineru-api`
 > - 如果您想了解更多有关`vllm`的参数使用方法,请参考 [vllm官方文档](https://docs.vllm.ai/en/latest/cli/serve.html)
+> - 如果您想了解更多有关`lmdeploy`的参数使用方法,请参考 [lmdeploy官方文档](https://lmdeploy.readthedocs.io/en/latest/llm/api_server.html)
 
 ## GPU 设备选择与配置
 
@@ -21,7 +22,7 @@
 >   ```bash
 >   CUDA_VISIBLE_DEVICES=1 mineru -p <input_path> -o <output_path>
 >   ```
-> - 这种指定方式对所有的命令行调用都有效,包括 `mineru`、`mineru-vllm-server`、`mineru-gradio` 和 `mineru-api`,且对`pipeline`、`vlm`后端均适用。
+> - 这种指定方式对所有的命令行调用都有效,包括 `mineru`、`mineru-openai-server`、`mineru-gradio` 和 `mineru-api`,且对`pipeline`、`vlm`后端均适用。
 
 ### 常见设备配置示例
 > [!TIP]
@@ -39,9 +40,9 @@
 > [!TIP]
 > 以下是一些可能的使用场景:
 > 
-> - 如果您有多张显卡,需要指定卡0和卡1,并使用多卡并行来启动`vllm-server`,可以使用以下命令: 
+> - 如果您有多张显卡,需要指定卡0和卡1,并使用多卡并行来启动`openai-server`,可以使用以下命令: 
 >   ```bash
->   CUDA_VISIBLE_DEVICES=0,1 mineru-vllm-server --port 30000 --data-parallel-size 2
+>   CUDA_VISIBLE_DEVICES=0,1 mineru-openai-server --engine vllm --port 30000 --data-parallel-size 2
 >   ```
 >   
 > - 如果您有多张显卡,需要在卡0和卡1上启动两个`fastapi`服务,并分别监听不同的端口,可以使用以下命令: