ModelPrésentéExterne

Genre Prediction

Music genre classifier trained on the Messy Mashup competition dataset.

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

TypeOtherVersionRevision 2eedd1dCClasse

Source du modèle

Type: Other
Taille du fichier: 41,4 MB
Version: vRevision 2eedd1d
Mis à jour: 26 sept. 2026
Téléchargements: 0
Source: Hugging Face

Description de la source

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()

Sources

1 source

Hugging FacePrincipalVersion 2eedd1dc45b03582cb14983cfaeb98b6d42bf240

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

Vérifié 29 août

Artefacts du modèle

1 artefact

kaggle/working/best_99.pth

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

Télécharger

Extraits de sources

2 extraits

Readme29 aoûthuggingface.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 aoûthuggingface.co/Kirandwip/Genre_prediction

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