Strengths
- Validated model templates tested on datasets provide reliable starting points for training.
- Native Intel GPU (XPU) support enables training without extra hardware setup.
- Supports distributed and mixed-precision training for scalability on multi-GPU systems.
- Direct export to OpenVINO IR and ONNX formats facilitates optimized deployment.
- Incremental learning allows adding new classes to pre-trained models.
Limitations
- Requires separate preparation of validation datasets for accurate model evaluation.
- Installation involves specific constraints and editable pip installs which may cause troubleshooting issues such as import errors.
- Focused exclusively on computer vision tasks with no explicit support for other domains like NLP.