Audio Classification
Transformers
Safetensors
English
audio-spectrogram-transformer
audio
ast
music
mood
Instructions to use guyPerry/audio-mood-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use guyPerry/audio-mood-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="guyPerry/audio-mood-classifier")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("guyPerry/audio-mood-classifier") model = AutoModelForAudioClassification.from_pretrained("guyPerry/audio-mood-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "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": "calm_melancholic", | |
| "1": "energetic_upbeat", | |
| "2": "moderate_neutral" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "calm_melancholic": 0, | |
| "energetic_upbeat": 1, | |
| "moderate_neutral": 2 | |
| }, | |
| "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": "5.13.1", | |
| "use_cache": false | |
| } |