# Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("dima806/classical_composer_classification-new")
model = AutoModelForAudioClassification.from_pretrained("dima806/classical_composer_classification-new")Quick Links
Currently, the model returns the confidence score that the input audio is created by one of the following classical composers found in MusicNet Dataset - a curated collection of 330 freely-licensed labeled classical music recordings - used for the training of this model:
More details in my Kaggle notebook and my Medium post.
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Model tree for dima806/classical_composer_classification-new
Base model
facebook/wav2vec2-base-960h
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="dima806/classical_composer_classification-new")