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metadata
title: Music Classification with MIT AST
emoji: 🎵
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.9.1
app_file: app.py
pinned: false
license: mit

Music Classification with MIT's AST Model 🎵

This Hugging Face Space demonstrates audio classification using MIT's Audio Spectrogram Transformer (AST) model. The model can identify various types of music, instruments, and sounds in audio files.

Features

  • Simple, user-friendly interface
  • Support for multiple audio formats (WAV, MP3, OGG, FLAC)
  • Top-5 predictions with confidence scores
  • Real-time processing

How to Use

  1. Click the "Upload Music File" button or drag and drop an audio file
  2. Wait a few seconds for the model to process the audio
  3. View the classification results with confidence scores

Model Details

This app uses the MIT/ast-finetuned-audioset-10-10-0.4593 model, which is trained on AudioSet and can recognize a wide variety of sounds and music styles. The model converts audio into spectrograms and uses a transformer architecture to classify the audio content.

Technical Notes

  • The model processes audio at 16kHz
  • Results show top 5 predictions with confidence scores
  • Processing is done on Hugging Face's infrastructure
  • No local installation required

Credits

  • Model: MIT AST
  • Interface: Gradio
  • Deployment: Hugging Face Spaces