salim4n/tfjs-dqn-test-1744654655889

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

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.