Audio Classification
Transformers
Safetensors
English
audio-spectrogram-transformer
music
speech
ast
Instructions to use Vyvo-Research/AST-Music-Classifier-82K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vyvo-Research/AST-Music-Classifier-82K with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Vyvo-Research/AST-Music-Classifier-82K")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("Vyvo-Research/AST-Music-Classifier-82K") model = AutoModelForAudioClassification.from_pretrained("Vyvo-Research/AST-Music-Classifier-82K") - Notebooks
- Google Colab
- Kaggle
File size: 715 Bytes
c715b5b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | {
"architectures": [
"ASTForAudioClassification"
],
"attention_probs_dropout_prob": 0.0,
"dtype": "float32",
"frequency_stride": 10,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.0,
"hidden_size": 768,
"id2label": {
"0": "music",
"1": "speech"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"label2id": {
"music": 0,
"speech": 1
},
"layer_norm_eps": 1e-12,
"max_length": 1024,
"model_type": "audio-spectrogram-transformer",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"num_mel_bins": 128,
"patch_size": 16,
"problem_type": "single_label_classification",
"qkv_bias": true,
"time_stride": 10,
"transformers_version": "4.57.1"
}
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