diff --git a/mteb-zh/readme.md b/mteb-zh/readme.md
index 4882092..364ff43 100644
--- a/mteb-zh/readme.md
+++ b/mteb-zh/readme.md
@@ -59,38 +59,29 @@ pip install -r requirements.txt
 ```
 2. 运行评测脚本
 ```bash
-# model_type: m3e_base, erlangshen, uer, d_meta_soul, openai, text2vec ...
-python run_mteb_zh <model_type> <model_name: Optional>
+python run_mteb_zh.py --model-type <model_type> --model-id <model_id: Optional>
 ```
 3. 查看帮助
 ```bash
-python run_mteb_zh --help
+python run_mteb_zh.py --help
 ```
 
 ### 示例
 
 评测 M3E-base 模型
 ```bash
-python run_mteb_zh sentence-transformer moka-ai/m3e-base
+python run_mteb_zh --model-type sentence_transformer --model-id moka-ai/m3e-base
 ```
 
 评测 UER 模型
 ```bash
-python run_mteb_zh uer uer/sbert-base-chinese-nli
+python run_mteb_zh --model-type sentence_transformer --model-id uer/sbert-base-chinese-nli
 ```
 
 评测 ErLangShen 模型
 ```bash
-python run_mteb_zh erlangshen
+python run_mteb_zh --model-type erlangshen
 ```
-case ModelType.m3e_small:
-    return SentenceTransformer('moka-ai/m3e-small')
-case ModelType.m3e_base:
-    return SentenceTransformer('moka-ai/m3e-base')
-case ModelType.d_meta_soul:
-    return SentenceTransformer('DMetaSoul/sbert-chinese-general-v2')
-case ModelType.uer:
-    return SentenceTransformer('uer/sbert-base-chinese-nli')
 
 ## 评测你的模型
 
diff --git a/mteb-zh/run_mteb_zh.py b/mteb-zh/run_mteb_zh.py
index ff971ec..33fd34b 100644
--- a/mteb-zh/run_mteb_zh.py
+++ b/mteb-zh/run_mteb_zh.py
@@ -30,24 +30,34 @@
 ]
 
 
+def filter_by_name(name: str):
+    return [task for task in default_tasks if task.description['name'] == name]   # type: ignore
+
+
+def filter_by_type(task_type: TaskType):
+    if task_type is TaskType.All:
+        return default_tasks
+    else:
+        return [task for task in default_tasks if task.description['type'] == task_type.value]  # type: ignore
+
+
 def main(
     model_type: Annotated[ModelType, typer.Option()],
     model_id: str | None = None,
-    model_name: str | None = None,
     task_type: TaskType = TaskType.Classification,
+    task_name: str | None = None,
     output_folder: Path = Path('results'),
 ):
     output_folder = Path(output_folder)
     model = load_model(model_type, model_id)
 
-    if task_type is TaskType.All:
-        tasks = default_tasks
+    if task_name:
+        tasks = filter_by_name(task_name)
     else:
-        tasks = [task for task in default_tasks if task.description['type'] == task_type.value]  # type: ignore
+        tasks = filter_by_type(task_type)
 
     evaluation = MTEB(tasks=tasks)
-    if model_name is None:
-        model_name = model_type.value + (f'-{model_id.replace("/", "-")}' if model_id else '')
+    model_name = model_type.value + (f'-{model_id.replace("/", "-")}' if model_id else '')
     evaluation.run(model, output_folder=str(output_folder / model_name))