Update README.md

README.md

@@ -34,7 +34,7 @@ Fine-tuned facebook/wav2vec2-large-xlsr-53 on Hindi and Marathi using the OpenSL
 ## Usage
  The model can be used directly (without a language model) as follows, assuming you have a dataset with Marathi text and audio_path fields:
 
-```
+```python
 import torch
 import torchaudio
 import librosa
@@ -65,8 +65,8 @@ print("Prediction:", processor.batch_decode(predicted_ids))
 print("Reference:", test_data["text"][:2])
 Evaluation
 The model can be evaluated as follows on 10% of the Marathi data on OpenSLR.
-```
-```
+
+```python
 import torchaudio
 from datasets import load_metric
 from transformers import Wav2Vec2Processor,Wav2Vec2ForCTC
@@ -81,7 +81,7 @@ model = Wav2Vec2ForCTC.from_pretrained("tanmaylaud/wav2vec2-large-xlsr-hindi-mar
 
 model.to("cuda")
 
-chars_to_ignore_regex = '[\\\\,\\\\?\\\\.\\\\!\\\\-\\\\;\\\\:\\\\"\\\\“\\\\%\\\\‘\\\\”\\\\�\\\\।]'
+chars_to_ignore_regex = '[\\\\\\\\,\\\\\\\\?\\\\\\\\.\\\\\\\\!\\\\\\\\-\\\\\\\\;\\\\\\\\:\\\\\\\\"\\\\\\\\“\\\\\\\\%\\\\\\\\‘\\\\\\\\”\\\\\\\\�\\\\\\\\।]'
 
 # Preprocessing the datasets.
 # We need to read the audio files as arrays