Improving the Unstructured Install Experience with ONNX

ONNX is a standard that facilitates the interoperability of machine learning models by converting them from various tools like PyTorch, TensorFlow, and Scikit-learn into a format with common operators, allowing them to be used across different platforms for training or inference. This standardization not only enables sharing and further development of models but also optimizes performance on target architectures with minimal modifications. In a practical application, the Detectron2 repository provides a script to export models to ONNX, requiring only a YAML file for model definition, which can then be utilized in the ONNX runtime environment across various hardware like CPUs, GPUs, or specialized devices. The Detectron2 model exported to ONNX is included in the Unstructured library from version 0.7.0, potentially resolving previous installation issues, with further enhancements and possibilities hinted at for future exploration.