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# TensorFlow.js Model
## Model Information
- Framework: TensorFlow.js
- Type: Deep Q-Network (DQN)
- Created by: IgnitionAI
## Model Format
This model is saved in TensorFlow.js format and can be loaded in two ways:
1. **LayersModel** (Default)
- Better for fine-tuning and training
- More flexible for model modifications
- Higher memory usage
- Slower inference
2. **GraphModel**
- Optimized for inference only
- Faster execution
- Lower memory usage
- Not suitable for training
## Usage
```javascript
import { loadModelFromHub } from '@ignitionai/backend-tfjs';
// Option 1: Load as LayersModel (for training/fine-tuning)
const layersModel = await loadModelFromHub(
'salim4n/tfjs-dqn-test-1744654655889',
'model/model.json',
false // graphModel = false for LayersModel
);
// Option 2: Load as GraphModel (for inference only)
const graphModel = await loadModelFromHub(
'salim4n/tfjs-dqn-test-1744654655889',
'model/model.json',
true // graphModel = true for GraphModel
);
// Run inference
const input = tf.tensor2d([[0.1, 0.2]]);
const output = model.predict(input);
```
## Features
- Automatic retry with exponential backoff
- Configurable retry attempts and delays
- Error handling and logging
- Support for both LayersModel and GraphModel
## Files
- `model.json`: Model architecture and configuration
- `weights.bin`: Model weights
- `README.md`: This documentation
## Repository
This model was uploaded via the IgnitionAI TensorFlow.js integration.
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