Update README.md

README.md

@@ -69,7 +69,7 @@ Users (both direct and downstream) should be made aware of the risks, biases and
 
 Use the code below to get started with the model.
 
-[### Running the model 
+### Running the model 
 
 <details>
 <summary> Click to expand </summary>
@@ -82,7 +82,6 @@ import torch
 import torchaudio
 
 model_id = "fastinom/ASR_fassy"
-# Load model and processor
 model = Wav2Vec2ForCTC.from_pretrained(model_id)
 processor = Wav2Vec2Processor.from_pretrained(model_id)
 
@@ -91,18 +90,12 @@ def load_audio(file_path):
     resampler = torchaudio.transforms.Resample(sampling_rate, 16000)
     speech = resampler(speech_array).squeeze().numpy()
     return speech
-# Example audio file path
 audio_file = "/content/drive/MyDrive/recordings/wavefiles/1.wa"#YOUR AUDIO PATH
 speech = load_audio(audio_file)
 
-# Preprocess the audio
 inputs = processor(speech, sampling_rate=16000, return_tensors="pt", padding=True)
-
-# Perform inference
 with torch.no_grad():
     logits = model(inputs.input_values).logits
-
-# Decode the output
 predicted_ids = torch.argmax(logits, dim=-1)
 transcription = processor.batch_decode(predicted_ids)
 print(transcription[0])