A Comprehensive Implementation Guide to ModelScope for Model Search, Inference, Fine-Tuning, Evaluation, and Export

a confusion matrix. We also test the model on new reviews to see how well it generalizes to unseen data.

Finally, we export our fine-tuned model for future use or sharing:

1. Local Saving: The model is saved locally in a specified directory.
2. ONNX Exportation: If available and supported, the model can be converted into ONNX format which allows for deployment across different platforms and devices.
3. ModelScope Hub Upload (Manual Step): Instructions are provided to upload the fine-tuned model to ModelScope's repository, making it accessible to others.

This comprehensive tutorial covers a wide range of functionalities within the ModelScope platform, from basic operations like downloading models and datasets to advanced tasks such as training, evaluating, and exporting models. It provides hands-on experience with key features that are essential for both beginners and experienced users looking to leverage ModelScope's extensive resources in their machine learning projects.

The tutorial concludes by summarizing all covered topics and providing a checklist of achievements, ensuring readers have gained proficiency in using ModelScope for various NLP and CV tasks.

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