ModelPublicadoExterno

Genre Prediction

Music genre classifier trained on the Messy Mashup competition dataset.

Fuentehuggingface.co/Kirandwip/Genre_prediction/tree/2eedd1dc45b03582cb14983cfaeb98b6d42bf240

TipoOtherVersiónRevision 2eedd1dCcalidad

Fuente del modelo

Tipo: Other
Tamaño del archivo: 41,4 MB
Versión: vRevision 2eedd1d
Actualizado: 26 sept 2026
Descargas: 0
Fuente: Hugging Face

Descripción de la fuente

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()

Fuentes

1 fuente

Hugging FacePrincipalVersión 2eedd1dc45b03582cb14983cfaeb98b6d42bf240

huggingface.co/Kirandwip/Genre_prediction/tree/2eedd1dc45b03582cb14983cfaeb98b6d42bf240

Verificado 29 ago

Artefactos del modelo

1 artefacto

kaggle/working/best_99.pth

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

Descargar

Extractos de fuentes

2 extractos

Readme29 agohuggingface.co/Kirandwip/Genre_prediction

--- 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() ```

Note29 agohuggingface.co/Kirandwip/Genre_prediction

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