How-To Guides
These walkthroughs illustrate how to test your ML models across different modalities: Tabular, Natural Language Processing (NLP), and Computer Vision (CV). Each walkthrough provides steps to run the examples using the bundled sample data in rime_trial/ or your own models and data.
These guides will make use of the rime-engine CLI, which is accessible through the Python package.
Be sure to complete Installation before proceeding!
Tabular
For ML tasks like Binary Classification, Multi-Class Classification, Regression, and Ranking.
Follow these comprehensive guides for walkthroughs of core RIME features:
Familiar with RIME and know what you need? See the tutorials below:
NLP
For ML tasks like Text Classification and Named Entity Recognition.
Follow these comprehensive guides for walkthroughs of core RIME features:
Familiar with RIME and know what you need? See the tutorials below:
CV
For ML tasks like Image Classification and Object Detection.
Follow these comprehensive guides for walkthroughs of core RIME features:
Familiar with RIME and know what you need? See the tutorials below:
Troubleshooting
Stuck? Check out our troubleshooting guides below.