adjust number and style in ainode

src/UserGuide/Master/Table/AI-capability/AINode_Upgrade_apache.md

@@ -163,8 +163,9 @@ It costs 1.615s
 
 1. AINode uses Transformers v4.56.2; avoid inheriting interfaces from older versions (<4.50).
 2. The model must inherit an AINode inference pipeline class (currently supports forecasting pipeline):
+    * iotdb-core/ainode/iotdb/ainode/core/inference/pipeline/basic_pipeline.py
+
     ```python
-    # iotdb-core/ainode/iotdb/ainode/core/inference/pipeline/basic_pipeline.py
     class BasicPipeline(ABC):
         def __init__(self, model_id, **model_kwargs):
             self.model_info = model_info

src/UserGuide/Master/Tree/AI-capability/AINode_Upgrade_apache.md

@@ -137,7 +137,7 @@ Total line number = 48
 
 1. AINode currently uses transformers v4.56.2, so when building the model, avoid inheriting from low versions (<4.50) interfaces;
 2. The model must inherit from a type of AINode inference task pipeline (currently supports forecast pipeline):
-    1. iotdb-core/ainode/iotdb/ainode/core/inference/pipeline/basic_pipeline.py
+   * iotdb-core/ainode/iotdb/ainode/core/inference/pipeline/basic_pipeline.py
 
    ```Python
    class BasicPipeline(ABC):
@@ -231,13 +231,13 @@ Total line number = 48
    }
    ```
 
-    1. Must specify the model's Config class and model class through auto_map;
-    2. Must integrate and specify the inference pipeline class;
-    3. For built-in (builtin) and user-defined (user_defined) models managed by AINode, the model category (model_type) also serves as a unique identifier. That is, the model category to be registered must not duplicate any existing model types.
+   * Must specify the model's Config class and model class through auto_map;
+   * Must integrate and specify the inference pipeline class; 
+   * For built-in (builtin) and user-defined (user_defined) models managed by AINode, the model category (model_type) also serves as a unique identifier. That is, the model category to be registered must not duplicate any existing model types.
 4. Ensure the model directory to be registered contains the following files, and the model configuration file name and weight file name are not customizable:
-    1. Model configuration file: config.json;
-    2. Model weight file: model.safetensors;
-    3. Model code: other .py files.
+   * Model configuration file: config.json; 
+   * Model weight file: model.safetensors; 
+   * Model code: other .py files.
 
 **The SQL syntax for registering a custom model is as follows:**
 

src/UserGuide/Master/Tree/AI-capability/AINode_Upgrade_timecho.md

@@ -217,7 +217,7 @@ IoTDB> show models
 
 1. AINode currently uses transformers version v4.56.2, so when building the model, it is necessary to **avoid inheriting low-version (<4.50) interfaces**;
 2. The model needs to inherit a type of AINode inference task pipeline (currently supports the forecasting pipeline):
-    1. iotdb-core/ainode/iotdb/ainode/core/inference/pipeline/basic\_pipeline.py
+   * iotdb-core/ainode/iotdb/ainode/core/inference/pipeline/basic\_pipeline.py
 
    ```Python
    class BasicPipeline(ABC):
@@ -311,13 +311,13 @@ IoTDB> show models
    }
    ```
 
-    1. Must specify the model Config class and model class through auto\_map;
-    2. Must integrate and specify the inference pipeline class;
-    3. For AINode-managed built-in (builtin) and custom (user\_defined) models, the model category (model\_type) also serves as a unique identifier. That is, the model category to be registered must not be duplicated with any existing model type. Models created through fine-tuning will inherit the model category of the original model.
+   * Must specify the model Config class and model class through auto\_map;
+   * Must integrate and specify the inference pipeline class;
+   * For AINode-managed built-in (builtin) and custom (user\_defined) models, the model category (model\_type) also serves as a unique identifier. That is, the model category to be registered must not be duplicated with any existing model type. Models created through fine-tuning will inherit the model category of the original model.
 4. Ensure that the model directory to be registered contains the following files, and the model configuration file name and weight file name are not customizable:
-    1. Model configuration file: config.json;
-    2. Model weight file: model.safetensors;
-    3. Model code: other .py files.
+   * Model configuration file: config.json;
+   * Model weight file: model.safetensors;
+   * Model code: other .py files.
 
 **The SQL syntax for registering a custom model is as follows:**
 

src/UserGuide/latest-Table/AI-capability/AINode_Upgrade_apache.md

@@ -163,8 +163,9 @@ It costs 1.615s
 
 1. AINode uses Transformers v4.56.2; avoid inheriting interfaces from older versions (<4.50).
 2. The model must inherit an AINode inference pipeline class (currently supports forecasting pipeline):
+    * iotdb-core/ainode/iotdb/ainode/core/inference/pipeline/basic_pipeline.py
+
     ```python
-    # iotdb-core/ainode/iotdb/ainode/core/inference/pipeline/basic_pipeline.py
     class BasicPipeline(ABC):
         def __init__(self, model_id, **model_kwargs):
             self.model_info = model_info