Getting Started

The AI Model Trainer is available as a cloud service or as a self-hosted solution. For the cloud service, simply sign up for an account and you're ready to go. For the self-hosted solution, follow the installation instructions below.

### Cloud Service

1. Sign up for an account at [bobo.tech](https://bobo.tech) 2. Navigate to the AI Model Trainer in your dashboard 3. Create a new project and you're ready to go

### Self-Hosted Solution

```bash # Clone the repository git clone https://github.com/bobo-tech/ai-model-trainer.git

# Install dependencies cd ai-model-trainer npm install

# Start the server npm start ```

Before training your first model, you'll need to configure your environment and set up your project. This includes selecting the appropriate compute resources, setting up data storage, and configuring access controls.

### Compute Resources

The AI Model Trainer supports various compute resources, including CPU, GPU, and TPU. For most applications, a GPU is recommended for faster training times.

### Data Storage

You'll need to configure data storage for your training data and model artifacts. The AI Model Trainer supports various storage options, including local storage, cloud storage (AWS S3, Google Cloud Storage), and database storage.

### Access Controls

If you're working in a team, you may want to configure access controls to manage who can view, edit, and deploy your models. The AI Model Trainer provides role-based access controls to help you manage permissions.