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music_genres_classification
dima806/music_genres_classification
music_genres_classification is a audio classification model from dima806. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
Music genre classification is a fundamental and versatile application in many various domains. Some possible use cases for music genre classification include:
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Aug 11, 2023
- Updated
- Oct 19, 2024
- SHA
- 5f71fb1e
Base models
Model card
From the Hugging Face model README
Music genre classification is a fundamental and versatile application in many various domains. Some possible use cases for music genre classification include:
- music recommendation systems;
- content organization and discovery;
- radio broadcasting and programming;
- music licensing and copyright management;
- music analysis and research;
- content tagging and metadata enrichment;
- audio identification and copyright protection;
- music production and creativity;
- healthcare and therapy;
- entertainment and gaming.
The model is trained based on publicly available dataset of labeled music data — GTZAN Dataset — that contains 1000 sample 30-second audio files evenly split among 10 genres:
- blues;
- classical;
- country;
- disco;
- hip-hop;
- jazz;
- metal;
- pop;
- reggae;
- rock.
The final code is available as a Kaggle notebook. See also my Medium article for more details.
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Aug 11, 2023
- Updated
- Oct 19, 2024