Update README.md

README.md

@@ -39,8 +39,7 @@ After fine-tuning, the model shows a 2.5% increase in transcription accuracy for
 # How to Use
 You can use this model directly with a simple API call in Hugging Face. Here is a Python code snippet for using the model:
 
-# python
-# Copy code
+```python
 from transformers import AutoModelForCTC, Wav2Vec2Processor
 
 model = AutoModelForCTC.from_pretrained("your-username/your-model-name")
@@ -52,6 +51,7 @@ input_audio = processor(path_to_audio_file, return_tensors="pt", padding=True)
 # Perform the transcription
 transcription = model.generate(**input_audio)
 print("Transcription:", transcription)
+```
 
 # Citation
 If you use this model in your research, please cite it as follows: