add an example in README.md;

Signed-off-by: lawrence-cj <[email protected]>

README.md

@@ -274,6 +274,7 @@ where each line of [`asset/samples_mini.txt`](asset/samples_mini.txt) contains a
 
 - 32GB VRAM is required for both 0.6B and 1.6B model's training
 
+### 1). Train with image-text pairs in directory
 We provide a training example here and you can also select your desired config file from [config files dir](configs/sana_config) based on your data structure.
 
 To launch Sana training, you will first need to prepare data in the following formats. [Here](asset/example_data) is an example for the data structure for reference.
@@ -310,6 +311,24 @@ bash train_scripts/train.sh \
   --train.train_batch_size=8
 ```
 
+### 2). Train with image-text pairs in directory
+We also provide conversion scripts to convert your data to the required format. You can refer to the [data conversion scripts](asset/data_conversion_scripts) for more details.
+
+```bash
+python tools/convert_ImgDataset_to_WebDatasetMS_format.py
+```
+
+Then Sana's training can be launched via
+```bash
+# Example of training Sana 0.6B with 512x512 resolution from scratch
+bash train_scripts/train.sh \
+  configs/sana_config/512ms/Sana_600M_img512.yaml \
+  --data.data_dir="[asset/example_data_tar]" \
+  --data.type=SanaWebDatasetMS \
+  --model.multi_scale=true \
+  --train.train_batch_size=32
+```
+
 # 💻 4. Metric toolkit
 
 Refer to [Toolkit Manual](asset/docs/metrics_toolkit.md).