diff --git a/docs/tutorials/how_to_convert_model.md b/docs/tutorials/how_to_convert_model.md
index eed327932..1623106d7 100644
--- a/docs/tutorials/how_to_convert_model.md
+++ b/docs/tutorials/how_to_convert_model.md
@@ -2,16 +2,17 @@
 
 <!-- TOC -->
 
-- [How to convert model](#how-to-convert-model)
-  - [How to convert models from Pytorch to other backends](#how-to-convert-models-from-pytorch-to-other-backends)
-    - [Prerequisite](#prerequisite)
-    - [Usage](#usage)
-    - [Description of all arguments](#description-of-all-arguments)
-    - [Example](#example)
-  - [How to evaluate the exported models](#how-to-evaluate-the-exported-models)
-  - [List of supported models exportable to other backends](#list-of-supported-models-exportable-to-other-backends)
-  - [Reminders](#reminders)
-  - [FAQs](#faqs)
+- [Tutorial : How to convert model](#how-to-convert-model)
+    - [How to convert models from Pytorch to BACKEND](#how-to-convert-models-from-pytorch-to-other-backends)
+        - [Prerequisite](#prerequisite)
+        - [Usage](#usage)
+        - [Description of all arguments](#description-of-all-arguments)
+        - [How to find the corresponding deployment config of a PyTorch model](#how-to-find-the-corresponding-deployment-config-of-a-pytorch-model)
+        - [Example](#example)
+    - [How to evaluate the exported models](#how-to-evaluate-the-exported-models)
+    - [List of supported models exportable to BACKEND](#list-of-supported-models-exportable-to-other-backends)
+    - [Reminders](#reminders)
+    - [FAQs](#faqs)
 
 <!-- TOC -->
 
@@ -58,6 +59,12 @@ python ./tools/deploy.py \
 - `--show` : Whether to show detection outputs.
 - `--dump-info` : Whether to output information for SDK.
 
+#### How to find the corresponding deployment config of a PyTorch model
+
+1. Find model's codebase folder in `configs/ `. Example, convert a yolov3 model you need to find `configs/mmdet` folder.
+2. Find model's task folder in `configs/codebase_folder/ `. Just like yolov3 model, you need to find `configs/mmdet/single-stage` folder.
+3. Find deployment config file in `configs/codebase_folder/task_folder/ `. Just like deploy yolov3 model you can use `configs/mmdet/single-stage/single-stage_onnxruntime_dynamic.py`.
+
 #### Example
 
 ```bash
diff --git a/docs/tutorials/how_to_write_config.md b/docs/tutorials/how_to_write_config.md
index 441efe50a..6ba02d95e 100644
--- a/docs/tutorials/how_to_write_config.md
+++ b/docs/tutorials/how_to_write_config.md
@@ -19,9 +19,10 @@ This tutorial describes how to write a config for model conversion and deploymen
   - [3. How to write backend config](#3-how-to-write-backend-config)
     - [Example](#example-4)
   - [4. A complete example of mmcls on TensorRT](#4-a-complete-example-of-mmcls-on-tensorrt)
-  - [5. How to write model config](#5-how-to-write-model-config)
-  - [6. Reminder](#6-reminder)
-  - [7. FAQs](#7-faqs)
+  - [5. The name rules of our deployment config](#5-the-name-rules-of-our-deployment-config)
+  - [6. How to write model config](#6-how-to-write-model-config)
+  - [7. Reminder](#6-reminder)
+  - [8. FAQs](#7-faqs)
 
 <!-- TOC -->
 
@@ -131,7 +132,7 @@ The backend config is mainly used to specify the backend on which model runs and
 backend_config = dict(
     type='tensorrt',
     common_config=dict(
-        fp16_mode=False, log_level=trt.Logger.INFO, max_workspace_size=1 << 30)
+        fp16_mode=False, log_level=trt.Logger.INFO, max_workspace_size=1 << 30),
     model_inputs=[
         dict(
             input_shapes=dict(
@@ -188,14 +189,33 @@ onnx_config = dict(
 partition_config = None
 ```
 
-### 5. How to write model config
+### 5. The name rules of our deployment config
+
+There is a specific naming convention for the filename of deployment config files.
+
+```bash
+(task name)_(partition)_(backend name)_(dynamic or static).py
+```
+
+- `task name`: Model's task type.
+- `partition`: Optional, whether partition model is supported.
+- `backend name`: Backend's name. Note if you use the quantization function, you need to indicate the quantization type. Just like `tensorrt_int8`.
+- `dynamic or static`: Dynamic or static export. Note if the backend needs explicit shape information, you need to add a description of input size with `height x width` format. Just like `dynamic-512x1024-2048x2048`, it means that the min input shape is `512x1024` and the max input shape is `2048x2048`.
+
+#### Example
+
+```
+single-stage_partition_tensorrt-int8_dynamic-320x320-1344x1344.py
+```
+
+### 6. How to write model config
 
 According to model's codebase, write the model config file. Model's config file is used to initialize the model, referring to [MMClassification](https://github.com/open-mmlab/mmclassification/blob/master/docs/tutorials/config.md), [MMDetection](https://github.com/open-mmlab/mmdetection/blob/master/docs_zh-CN/tutorials/config.md), [MMSegmentation](https://github.com/open-mmlab/mmsegmentation/blob/master/docs_zh-CN/tutorials/config.md), [MMOCR](https://github.com/open-mmlab/mmocr/tree/main/configs), [MMEditing](https://github.com/open-mmlab/mmediting/blob/master/docs_zh-CN/config.md).
 
-### 6. Reminder
+### 7. Reminder
 
 None
 
-### 7. FAQs
+### 8. FAQs
 
 None