Update README.md

README.md

@@ -7,10 +7,13 @@ Models trained from [VITS-fast-fine-tuning](https://github.com/Plachtaa/VITS-fas
 - Three speakers: laoliang (老梁), specialweek, zhongli.
 - The model is based on the C+J base model and trained on a single NVIDIA 3090 with 300 epochs. It takes about 4.5 hours in total.
 - During training, we use a single long audio of laoliang (~5 minutes) with auxiliary data as training data.
-- After downloading models, you need to move finetune_speaker.json and G_latest.pth to _/path/to/ VITS-fast-fine-tuning_.
-- Following [the official instruction](https://github.com/Plachtaa/VITS-fast-fine-tuning/blob/main/LOCAL.md), install required libraries.
-- On inference, you can run your local gradio application via _python VC_inference.py --model_dir ./G_latest.pth --share True_
 
+How to run the model?
+- Follow [the official instruction](https://github.com/Plachtaa/VITS-fast-fine-tuning/blob/main/LOCAL.md), install required libraries.
+- Download models and move _finetune_speaker.json_ and _G_latest.pth_ to _/path/to/ VITS-fast-fine-tuning_.
+- Run _python VC_inference.py --model_dir ./G_latest.pth --share True_ to start a local gradio inference demo.
+
+File structure
 ```bash
 VITS-fast-fine-tuning
 ├───VC_inference.py