FrWhisper

import torch
from transformers import WhisperProcessor, WhisperForConditionalGeneration

# Load model and processor
processor = WhisperProcessor.from_pretrained("aihpi/FrWhisper")
model = WhisperForConditionalGeneration.from_pretrained("aihpi/FrWhisper")

# Process audio
def transcribe_french(audio_path):
    # Load and preprocess audio (16kHz)
    import librosa
    audio, sr = librosa.load(audio_path, sr=16000)
    
    # Process with model
    input_features = processor(audio, sampling_rate=16000, return_tensors="pt").input_features
    
    # Generate transcription
    with torch.no_grad():
        predicted_ids = model.generate(input_features, language="fr", task="transcribe")
    
    # Decode results
    transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
    return transcription

# Example usage
transcription = transcribe_french("french_audio.wav")
print(transcription)