Examples and tutorials
Notebook examples
These examples use mb.deploy to create Modelbit deployments from a Python notebook like Hex, Colab, or Jupyter. If this is your first deployment, start with the getting started guide for Python notebooks.
- Sentence segmentation with spaCy NLP: Use spaCy to segment paragraphs into sentences.
- Time series forecasting with Prophet: Perform single and batch inferences with time series data.
- Image segmentation with SAM: Use Segment Anything to detect the outlines of objects in images.
- Image segmentation with SAM 2: Use Segment Anything 2 to detect the outlines of objects in images.
- Image promoting with LLaVa: Use LLaVa to answer questions about what's in images.
Git examples
These examples use Git to git push Modelbit deployments from your terminal. If this is your first deployment, start with the getting started guide for Git.
- Flower classification with XGBoost: Deploy a pickled model that predicts flower types.
- Batch classification with DataFrames: Use DataFrame mode for batch inference request on an XGBoost model.
- Image segmentation with SAM: Use Segment Anything to detect the outlines of objects in images.
Tips & tricks
- Optimizing deployment performance: Techniques for reducing latency and increasing throughput.