SleepyJesse/ai_music_large
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How to use AI-Music-Detection/ai_music_detection_large_10.24s with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="AI-Music-Detection/ai_music_detection_large_10.24s") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("AI-Music-Detection/ai_music_detection_large_10.24s")
model = AutoModelForAudioClassification.from_pretrained("AI-Music-Detection/ai_music_detection_large_10.24s")This model was trained from mit/ast-finetuned-audioset-10-10-0.4593 on the SleepyJesse/ai_music_large dataset.
The model was trained with max_length = 1024, which is 10.24 seconds.
This model is used to classify a given music piece is AI-generated or human-composed.
The SleepyJesse/ai_music_large dataset was used, with 80% train/test split, and 0.8 probability for audio data augmentation.
See the file ai_music_detection_new_large.ipynb and training metrics.
The following hyperparameters were used during training:
Base model
MIT/ast-finetuned-audioset-10-10-0.4593