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| import torch | |
| from transformers import Wav2Vec2FeatureExtractor, AutoModelForAudioClassification | |
| import numpy as np | |
| def check_model(): | |
| model_name = "nii-yamagishilab/mms-300m-anti-deepfake" | |
| feature_extractor_name = "facebook/mms-300m" | |
| print(f"Verifying load for: {model_name}") | |
| try: | |
| feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(feature_extractor_name) | |
| model = AutoModelForAudioClassification.from_pretrained(model_name) | |
| print("Success! Model and Extractor loaded.") | |
| print(f"Classes: {model.config.id2label}") | |
| except Exception as e: | |
| print(f"Failed: {e}") | |
| if __name__ == "__main__": | |
| check_model() | |