Update demo.mdx

chapters/en/chapter4/demo.mdx

@@ -1,9 +1,9 @@
 # Build a demo with Gradio
 
-In this final section on audio classification, we'll build a [Gradio]((https://gradio.app)) demo to showcase the music
+In this final section on audio classification, we'll build a [Gradio](https://gradio.app) demo to showcase the music
 classification model that we just trained on the [GTZAN](https://huggingface.co/datasets/marsyas/gtzan) dataset. The first
 thing to do is load up the fine-tuned checkpoint using the `pipeline()` class - this is very familiar now from the section
-on [pre-trained models](../classification_models). You can change the `model_id` to the namespace of your fine-tuned model
+on [pre-trained models](classification_models). You can change the `model_id` to the namespace of your fine-tuned model
 on the Hugging Face Hub:
 
 ```python