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Genre Prediction

Music genre classifier trained on the Messy Mashup competition dataset.

TipoOtherVersãoRevision 2eedd1dCnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
41,4 MB
Versão
vRevision 2eedd1d
Atualizado
26 de set. de 2026
Downloads
0
Fonte
Hugging Face

Descrição da fonte

Genre Classification — EfficientNet-B3

Music genre classifier trained on the Messy Mashup competition dataset.

Classes

blues, classical, country, disco, hiphop, jazz, metal, pop, reggae, rock

Architecture

EfficientNet-B3 fine-tuned on mel spectrograms (128 mel bins, 5s clips, 22050 Hz).

How to load

import torch
from torchvision import models
from huggingface_hub import hf_hub_download

model_path = hf_hub_download(repo_id="Kirandwip/Genre_prediction", filename="perfection_model_99.pth")

model = models.efficientnet_b3(weights=None)
model.classifier[1] = torch.nn.Linear(model.classifier[1].in_features, 10)
model.load_state_dict(torch.load(model_path, map_location="cpu"))
model.eval()

Fontes

1 fonte
Hugging FacePrimárioVersão 2eedd1dc45b03582cb14983cfaeb98b6d42bf240
huggingface.co/Kirandwip/Genre_prediction/tree/2eedd1dc45b03582cb14983cfaeb98b6d42bf240

Verificado 29 de ago.

Artefatos de modelo

1 artefato

kaggle/working/best_99.pth

pth · 41,4 MB · SHA-256 7670c3dc42cc…5cf7 · Hugging Face

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Trechos de fonte

2 trechos

--- language: en tags: - audio-classification - music-genre - efficientnet - pytorch license: mit --- # Genre Classification — EfficientNet-B3 Music genre classifier trained on the Messy Mashup competition dataset. ## Classes blues, classical, country, disco, hiphop, jazz, metal, pop, reggae, rock ## Architecture EfficientNet-B3 fine-tuned on mel spectrograms (128 mel bins, 5s clips, 22050 Hz). ## How to load ```python import torch from torchvision import models from huggingface_hub import hf_hub_download model_path = hf_hub_download(repo_id="Kirandwip/Genre_prediction", filename="perfection_model_99.pth") model = models.efficientnet_b3(weights=None) model.classifier[1] = torch.nn.Linear(model.classifier[1].in_features, 10) model.load_state_dict(torch.load(model_path, map_location="cpu")) model.eval() ```

Source context: 0 downloads · 0 likes · Pipeline audio-classification · Repo Kirandwip/Genre_prediction