Langchain-Chatchat/docs/StartOption.md

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#### 项目启动选项
```test
usage: langchina-ChatGLM [-h] [--no-remote-model] [--model MODEL] [--lora LORA] [--model-dir MODEL_DIR] [--lora-dir LORA_DIR] [--cpu] [--auto-devices] [--gpu-memory GPU_MEMORY [GPU_MEMORY ...]] [--cpu-memory CPU_MEMORY]
[--load-in-8bit] [--bf16]
基于langchain和chatGML的LLM文档阅读器
options:
-h, --help show this help message and exit
--no-remote-model remote in the model on loader checkpoint, if your load local model to add the ` --no-remote-model`
--model MODEL Name of the model to load by default.
--lora LORA Name of the LoRA to apply to the model by default.
--model-dir MODEL_DIR
Path to directory with all the models
--lora-dir LORA_DIR Path to directory with all the loras
--cpu Use the CPU to generate text. Warning: Training on CPU is extremely slow.
--auto-devices Automatically split the model across the available GPU(s) and CPU.
--gpu-memory GPU_MEMORY [GPU_MEMORY ...]
Maxmimum GPU memory in GiB to be allocated per GPU. Example: --gpu-memory 10 for a single GPU, --gpu-memory 10 5 for two GPUs. You can also set values in MiB like --gpu-memory 3500MiB.
--cpu-memory CPU_MEMORY
Maximum CPU memory in GiB to allocate for offloaded weights. Same as above.
--load-in-8bit Load the model with 8-bit precision.
--bf16 Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.
```
#### 示例
- 1、加载本地模型
```text
--model-dir 本地checkpoint存放文件夹
--model 模型名称
--no-remote-model 不从远程加载模型
```
```shell
$ python cli_demo.py --model-dir /media/mnt/ --model chatglm-6b --no-remote-model
```
- 2、低精度加载模型
```text
--model-dir 本地checkpoint存放文件夹
--model 模型名称
--no-remote-model 不从远程加载模型
--load-in-8bit 以8位精度加载模型
```
```shell
$ python cli_demo.py --model-dir /media/mnt/ --model chatglm-6b --no-remote-model --load-in-8bit
```
- 3、使用cpu预测模型
```text
--model-dir 本地checkpoint存放文件夹
--model 模型名称
--no-remote-model 不从远程加载模型
--cpu 使用CPU生成文本。警告CPU上的训练非常缓慢。
```
```shell
$ python cli_demo.py --model-dir /media/mnt/ --model chatglm-6b --no-remote-model --cpu
```
- 3、加载lora微调文件
```text
--model-dir 本地checkpoint存放文件夹
--model 模型名称
--no-remote-model 不从远程加载模型
--lora-dir 本地lora存放文件夹
--lora lora名称
```
```shell
$ python cli_demo.py --model-dir /media/mnt/ --model chatglm-6b --no-remote-model --lora-dir /media/mnt/loras --lora chatglm-step100
```