from transformers import WhisperProcessor, WhisperForConditionalGeneration
import librosa 
import torch 


model_name = "basharalrfooh/whisper-samll-quran"
processor = WhisperProcessor.from_pretrained(model_name)
model = WhisperForConditionalGeneration.from_pretrained(model_name)
model.config.forced_decoder_ids = None


audio_file = "Your .wav file"

speech_array, sampling_rate = librosa.load(audio_file, sr=16000)

inputs = processor(speech_array, return_tensors="pt", sampling_rate=sampling_rate)

with torch.no_grad():
    predicted_ids = model.generate(inputs["input_features"])

# Decode token IDs to text
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)

print(f"Transcription: {transcription}")
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