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
| pipeline_tag: audio-classification | |
| library_name: transformers | |
| language: en | |
| tags: | |
| - audio | |
| - audio-classification | |
| - ast | |
| - music | |
| - mood | |
| license: apache-2.0 | |
| # Audio Mood Classifier | |
| Fine-tuned [Audio Spectrogram Transformer (AST)](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) for music mood classification. | |
| ## Classes | |
| | Label | Description | | |
| |---|---| | |
| | calm_melancholic | Slow, introspective, melancholic | | |
| | moderate_neutral | Balanced, mid-energy, neutral feel | | |
| | energetic_upbeat | Fast, high-energy, upbeat | | |
| ## Usage | |
| ```python | |
| from transformers import pipeline | |
| classifier = pipeline("audio-classification", model="guyPerry/audio-mood-classifier") | |
| result = classifier("song.mp3") | |
| ``` | |