Instructions to use btehubsolutions/alertdrive-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use btehubsolutions/alertdrive-model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://btehubsolutions/alertdrive-model") - Notebooks
- Google Colab
- Kaggle
File size: 630 Bytes
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license: apache-2.0
tags:
- image-classification
- keras
- tensorflow
- alertdrive
---
# AlertDrive AI Model
Binary classification model for driver alert detection.
## Model Details
- **Input:** 224x224x3 RGB images
- **Output:** Binary classification (Alert/No Alert)
- **Framework:** TensorFlow/Keras
## Usage
```python
from huggingface_hub import hf_hub_download
import tensorflow as tf
# Download model
model_path = hf_hub_download(repo_id="YOUR_USERNAME/alertdrive-model", filename="alertdrive_ai.keras")
model = tf.keras.models.load_model(model_path)
# Make prediction
prediction = model.predict(image_array)
```
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