Update README.md

README.md

@@ -5,27 +5,26 @@ language:
 Whisper ASR for Kyrgyz Language is an automatic speech recognition (ASR) solution customized for the Kyrgyz language. It is based on the pre-trained Whisper model and has undergone fine-tuning and adaptation to accurately transcribe Kyrgyz speech, taking into account its specific phonetic intricacies.
 
 To run the model, first install: 
-
+```bash
 !pip install datasets>=2.6.1
 !pip install git+https://github.com/huggingface/transformers
 !pip install librosa
 !pip install evaluate>=0.30
 !pip install jiwer
 !pip install gradio==3.50.2
-
-
+```
 
 Linking the notebook to the Hub is straightforward - it simply requires entering your Hub authentication token when prompted. 
-
+```python
 from huggingface_hub import notebook_login
 
 notebook_login()
-
+```
 
 Now that we've fine-tuned our model, we can build a demo to show off its ASR capabilities! We'll use 🤗 Transformers pipeline, which will take care of the entire ASR pipeline, right from pre-processing the audio inputs to decoding the model predictions. We'll build our interactive demo with Gradio. Gradio is arguably the most straightforward way of building machine learning demos; with Gradio, we can build a demo in just a matter of minutes!
 
 Running the example below will generate a Gradio demo where we can record speech through the microphone of our computer and input it to our fine-tuned Whisper model to transcribe the corresponding text:
-
+```python
 from transformers import pipeline
 import gradio as gr
 
@@ -44,4 +43,4 @@ iface = gr.Interface(
 )
 
 iface.launch()
-
+```