GUI

GUI Model with Threading

To run the QELM GUI, execute:

python QelmGUI.py

This launches an intuitive interface for:

Selecting Datasets: Choose between synthetic or real datasets for training.
Training with Live Progress Updates: Monitor training progress with real-time logs and progress bars.
Running Inference: Input tokens and generate outputs interactively.
Managing Token Mappings: View and manage token-to-ID mappings.
Resource Monitoring: View real-time CPU usage and estimate remaining training time.
Save/Load Models: Save trained models or load existing ones for further use.

Key GUI Features:

Real-time Progress Bars: For gradient computations and overall training progress.
System Resource Usage (CPU/GPU): Display current CPU usage and guidance on GPU monitoring.
Interactive Logs: Provides feedback and error monitoring in real-time.
Control Buttons: Options to save/load models, stop training gracefully, or halt immediately.