Autogguf

Added
- Dynamic KV override functionality
- Improved CUDA checking ability and extraction to the backend folder
- Scrollable area for KV overrides with add/delete capabilities

Changed
- Enhanced visibility and usability of Output Tensor Type and Token Embedding Type options
- Refactored code for better modularity and reduced circular dependencies

Fixed
- Behavior of Output Tensor Type and Token Embedding Type dropdown menus
- Various minor UI inconsistencies

Added
- Windows binary (created using PyInstaller)

Fixed
- Issue where quantization errored with "AutoGGUF does not have x attribute"

Added
- Initial release
- GUI interface for automated GGUF model quantization
- System resource monitoring (RAM and CPU usage)
- Llama.cpp backend selection and management
- Automatic download of llama.cpp releases from GitHub
- Model selection from local directory
- Comprehensive quantization options
- Task list for managing multiple quantization jobs
- Real-time log viewing for quantization tasks
- IMatrix generation feature with customizable settings
- GPU offload settings for IMatrix generation
- Context menu for task management
- Detailed model information dialog
- Error handling and user notifications
- Confirmation dialogs for task deletion and application exit