fix zsh install (modelscope#735)

README.md

@@ -140,11 +140,11 @@ SWIFT runs in the Python environment. Please ensure your Python version is highe
 
 ```shell
 # Full capabilities
-pip install ms-swift[all] -U
+pip install 'ms-swift[all]' -U
 # LLM only
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 # AIGC only
-pip install ms-swift[aigc] -U
+pip install 'ms-swift[aigc]' -U
 # Adapters only
 pip install ms-swift -U
 ```
@@ -154,7 +154,7 @@ pip install ms-swift -U
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 ```
 
 SWIFT depends on torch>=1.13, recommend torch>=2.0.0.

README_CN.md

@@ -141,11 +141,11 @@ SWIFT在Python环境中运行。请确保您的Python版本高于3.8。
 
 ```shell
 # 全量能力
-pip install ms-swift[all] -U
+pip install 'ms-swift[all]' -U
 # 仅使用LLM
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 # 仅使用AIGC
-pip install ms-swift[aigc] -U
+pip install 'ms-swift[aigc]' -U
 # 仅使用Adapters
 pip install ms-swift -U
 ```
@@ -155,7 +155,7 @@ pip install ms-swift -U
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 ```
 
 SWIFT依赖torch>=1.13，建议torch>=2.0.0。

docs/source/GetStarted/SWIFT安装.md

@@ -6,11 +6,11 @@
 
 ```shell
 # 全量能力
-pip install ms-swift[all] -U
+pip install 'ms-swift[all]' -U
 # 仅使用LLM
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 # 仅使用AIGC
-pip install ms-swift[aigc] -U
+pip install 'ms-swift[aigc]' -U
 # 仅使用adapters
 pip install ms-swift -U
 ```
@@ -20,7 +20,7 @@ pip install ms-swift -U
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[all]
+pip install -e '.[all]'
 ```
 
 ## Notebook环境

docs/source/LLM/Agent微调最佳实践.md

@@ -21,7 +21,7 @@ pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 # 安装ms-swift
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 
 # 环境对齐 (通常不需要运行. 如果你运行错误, 可以跑下面的代码, 仓库使用最新环境测试)
 pip install -r requirements/framework.txt  -U

docs/source/LLM/Grok训练和推理.md

@@ -13,7 +13,7 @@
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 ```
 
 ## 微调

docs/source/LLM/LLM人类对齐训练文档.md

@@ -11,7 +11,7 @@ pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 # 安装ms-swift
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 
 # 环境对齐 (通常不需要运行. 如果你运行错误, 可以跑下面的代码, 仓库使用最新环境测试)
 pip install -r requirements/framework.txt  -U

docs/source/LLM/LLM微调文档.md

@@ -17,7 +17,7 @@ pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 # 安装ms-swift
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 
 # 如果你想要使用deepspeed.
 pip install deepspeed -U

docs/source/LLM/LLM推理文档.md

@@ -12,7 +12,7 @@ GPU设备: A10, 3090, V100, A100均可.
 # 设置pip全局镜像 (加速下载)
 pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 # 安装ms-swift
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # 如果你想要使用基于auto_gptq的模型进行推理.
 # 使用auto_gptq的模型: `https://github.com/modelscope/swift/blob/main/docs/source/LLM/支持的模型和数据集.md#模型`

docs/source/LLM/LLM评测文档.md

@@ -54,7 +54,7 @@ pip install ms-swift[eval] -U
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[eval]
+pip install -e '.[eval]'
 ```
 
 ## 评测

docs/source/LLM/LLM量化文档.md

@@ -14,7 +14,7 @@ GPU设备: A10, 3090, V100, A100均可.
 # 设置pip全局镜像 (加速下载)
 pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 # 安装ms-swift
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # 使用awq量化:
 # autoawq和cuda版本有对应关系，请按照`https://github.com/casper-hansen/AutoAWQ`选择版本

docs/source/LLM/Qwen1.5全流程最佳实践.md

@@ -21,7 +21,7 @@
 
 ## 环境准备
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # autoawq和cuda版本有对应关系，请按照`https://github.com/casper-hansen/AutoAWQ`选择版本
 pip install autoawq

docs/source/LLM/VLLM推理加速与部署.md

@@ -15,7 +15,7 @@ GPU设备: A10, 3090, V100, A100均可.
 # 设置pip全局镜像 (加速下载)
 pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 # 安装ms-swift
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # vllm与cuda版本有对应关系，请按照`https://docs.vllm.ai/en/latest/getting_started/installation.html`选择版本
 pip install vllm -U

docs/source/LLM/自我认知微调最佳实践.md

@@ -15,7 +15,7 @@
 # 设置pip全局镜像 (加速下载)
 pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 # 安装ms-swift
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # 环境对齐 (通常不需要运行. 如果你运行错误, 可以跑下面的代码, 仓库使用最新环境测试)
 pip install -r requirements/framework.txt  -U

docs/source/Multi-Modal/cogvlm最佳实践.md

@@ -10,7 +10,7 @@
 
 ## 环境准备
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 ```
 
 ## 推理

docs/source/Multi-Modal/deepseek-vl最佳实践.md

@@ -10,7 +10,7 @@
 
 ## 环境准备
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 ```
 
 ## 推理

docs/source/Multi-Modal/internlm-xcomposer2最佳实践.md

@@ -10,7 +10,7 @@
 
 ## 环境准备
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 ```
 
 ## 推理

docs/source/Multi-Modal/llava最佳实践.md

@@ -12,7 +12,7 @@
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 ```
 
 ## 推理

docs/source/Multi-Modal/minicpm-v-2最佳实践.md

@@ -10,7 +10,7 @@
 
 ## 环境准备
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 ```
 
 ## 推理

docs/source/Multi-Modal/minicpm-v最佳实践.md

@@ -11,7 +11,7 @@
 
 ## 环境准备
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 ```
 
 模型链接:

docs/source/Multi-Modal/mplug-owl2最佳实践.md

@@ -13,7 +13,7 @@
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 ```
 
 模型链接:

docs/source/Multi-Modal/qwen-audio最佳实践.md

@@ -9,7 +9,7 @@
 
 ## 环境准备
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 ```
 
 ## 推理

docs/source/Multi-Modal/qwen-vl最佳实践.md

@@ -10,7 +10,7 @@
 
 ## 环境准备
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 ```
 
 ## 推理

docs/source/Multi-Modal/yi-vl最佳实践.md

@@ -12,7 +12,7 @@
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 ```
 
 ## 推理

docs/source_en/GetStarted/Installation.md

@@ -6,11 +6,11 @@ You can use pip to install:
 
 ```shell
 # Full capabilities
-pip install ms-swift[all] -U
+pip install 'ms-swift[all]' -U
 # Only use LLM
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 # Only use AIGC
-pip install ms-swift[aigc] -U
+pip install 'ms-swift[aigc]' -U
 # Only use adapters
 pip install ms-swift -U
 ```
@@ -20,7 +20,7 @@ pip install ms-swift -U
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[all]
+pip install -e '.[all]'
 ```
 
 ## Notebook Environment

docs/source_en/LLM/Agent-best-practice.md

@@ -19,7 +19,7 @@ SWIFT supports open-source models, especially small and medium-sized models (7B,
 # Install ms-swift
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 
 # Align environment (usually don't need to run. If you get errors, you can run the code below, the repo tests with the latest environment)
 pip install -r requirements/framework.txt  -U

docs/source_en/LLM/Grok-1-best-practice.md

@@ -11,7 +11,7 @@ This documentation introduces the process of finetuning and inferencing the Grok
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 ```
 
 ## Finetuning

docs/source_en/LLM/LLM-eval.md

@@ -54,7 +54,7 @@ or install from source code:
 ```shell
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[eval]
+pip install -e '.[eval]'
 ```
 
 ## Evaluation

docs/source_en/LLM/LLM-fine-tuning.md

@@ -14,7 +14,7 @@ GPU devices: A10, 3090, V100, A100 are all suitable.
 # Install ms-swift
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 
 # If you want to use deepspeed.
 pip install deepspeed -U

docs/source_en/LLM/LLM-inference.md

@@ -10,7 +10,7 @@ If you want to use vllm for inference acceleration, you can check out [VLLM Infe
 GPU devices: A10, 3090, V100, A100 are all supported.
 ```bash
 # Install ms-swift
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # If you want to use models based on auto_gptq for inference.
 # Models using auto_gptq: `https://github.com/modelscope/swift/blob/main/docs/source/LLM/Supported Models and Datasets.md#Models`

docs/source_en/LLM/LLM-quantization.md

@@ -11,7 +11,7 @@ Swift supports using AWQ and GPTQ techniques to quantize models. These two quant
 GPU devices: A10, 3090, V100, A100 are all supported.
 ```bash
 # Install ms-swift
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # Using AWQ quantization:
 # AutoAWQ and CUDA versions have a corresponding relationship, please select the version according to `https://github.com/casper-hansen/AutoAWQ`

docs/source_en/LLM/Qwen1.5-best-practice.md

@@ -19,7 +19,7 @@ This introduces how to perform inference, self-cognition fine-tuning, quantizati
 
 ## Environment Preparation
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # autoawq version corresponds to cuda version, please choose based on `https://github.com/casper-hansen/AutoAWQ`
 pip install autoawq

docs/source_en/LLM/RLHF.md

@@ -10,7 +10,7 @@ GPU devices: A10, 3090, V100, A100 are all acceptable. For GPUs with memory <=24
 # Install ms-swift
 git clone https://github.com/modelscope/swift.git
 cd swift
-pip install -e .[llm]
+pip install -e '.[llm]'
 
 # Environment alignment (usually not necessary. If you encounter errors, you can run the following code, the repository uses the latest environment for testing)
 pip install -r requirements/framework.txt  -U

docs/source_en/LLM/Self-cognition-best-practice.md

@@ -14,7 +14,7 @@ Fine-tune your own large model in just 10 minutes!
 # Set the global pip mirror (for faster downloads)
 pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 # Install ms-swift
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # Environment alignment (usually not necessary to run. If you encounter errors, you can run the following code to test with the latest environment in the repository)
 pip install -r requirements/framework.txt  -U
@@ -122,7 +122,7 @@ Fine-tune your own large model in just 10 minutes!
 # Set up the global pip mirror (for faster downloading)
 pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 # Install ms-swift
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # Align the environment (usually not necessary to run. If you get an error, you can run the following code, which has been tested with the latest environment in the repository)
 pip install -r requirements/framework.txt  -U

docs/source_en/LLM/VLLM-inference-acceleration-and-deployment.md

@@ -12,7 +12,7 @@ GPU devices: A10, 3090, V100, A100 are all supported.
 # Set pip global mirror (speeds up downloads)
 pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
 # Install ms-swift
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 
 # vllm version corresponds to cuda version, please select version according to `https://docs.vllm.ai/en/latest/getting_started/installation.html`
 pip install vllm -U

docs/source_en/Multi-Modal/cogvlm-best-practice.md

@@ -8,7 +8,7 @@
 
 ## Environment Setup
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 ```
 
 ## Inference

docs/source_en/Multi-Modal/deepseek-vl-best-practice.md

@@ -8,7 +8,7 @@
 
 ## Environment Preparation
 ```shell
-pip install ms-swift[llm] -U
+pip install 'ms-swift[llm]' -U
 ```
 
 ## Inference