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GlowLED
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wav2vec2-gtzan

Audio Classification
Transformers
Safetensors
wav2vec2
gtzan
music
fine-tuned
Model card Files
xet
 Community
How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("audio-classification", model="GlowLED/wav2vec2-gtzan")
# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification

processor = AutoProcessor.from_pretrained("GlowLED/wav2vec2-gtzan")
model = AutoModelForAudioClassification.from_pretrained("GlowLED/wav2vec2-gtzan", device_map="auto")
Quick Links

wav2vec2-gtzan

Fine-tuned facebook/wav2vec2-base for GTZAN music-genre classification (10 classes). Trained with 15s-window augmentation on sanchit-gandhi/gtzan; song-level accuracy 0.92 (window 0.8894). Use with AutoModelForAudioClassification.

Metrics

  • accuracy: 0.92

Usage 

# audio-classification
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Safetensors
Model size
94.6M params
Tensor type
F32
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