Update README.md

README.md

@@ -76,19 +76,19 @@ Use the code below to get started with the model.
 from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 import torch
 import torchaudio
-```python
+
 model_id = "fastinom/ASR_fassy"
 model = Wav2Vec2ForCTC.from_pretrained(model_id)
 processor = Wav2Vec2Processor.from_pretrained(model_id)
-```python
+
 def load_audio(file_path):
     speech_array, sampling_rate = torchaudio.load(file_path)
     resampler = torchaudio.transforms.Resample(sampling_rate, 16000)
     speech = resampler(speech_array).squeeze().numpy()
     return speech
-audio_file = "/content/drive/MyDrive/recordings/wavefiles/1.wa"#YOUR AUDIO PATH
+audio_file = "/content/drive/MyDrive/recordings/wavefiles/1.wav"
 speech = load_audio(audio_file)
-```python
+
 inputs = processor(speech, sampling_rate=16000, return_tensors="pt", padding=True)
 with torch.no_grad():
     logits = model(inputs.input_values).logits