Instructions to use FatimahAlzahrani/quran_maqam_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use FatimahAlzahrani/quran_maqam_classification with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://FatimahAlzahrani/quran_maqam_classification") - Notebooks
- Google Colab
- Kaggle
Quranic Maqam Classification using Deep Learning
Model Description
This is a deep learning model trained using TensorFlow/Keras and saved as an .h5 file. It is designed for classifying Quranic maqams.
Model Details
- Architecture: ANN
- Framework: TensorFlow / Keras
- Input Shape: (478, 26)
- Dataset: Maqam-478 Dataset
How to Use
Install Dependencies
pip install tensorflow huggingface_hub
Load Model from Hugging Face
from huggingface_hub import hf_hub_download
import tensorflow as tf
model_path = hf_hub_download(repo_id="FatimahAlzahrani/quran_maqam_classification", filename="model.h5")
model = tf.keras.models.load_model(model_path)
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