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Important
This feature is in Public Preview.
AI Runtime provides serverless GPU compute for inference, training, and fine-tuning AI and deep learning models. The pages below group example notebooks by task: large language models, computer vision, recommender systems, classic ML, and multi-GPU distributed training.
| Task | Description |
|---|---|
| Large language models (LLMs) | Examples for large language model batch inference and fine-tuning, including parameter-efficient methods. |
| Computer vision | Examples for computer vision tasks including object detection and image classification. |
| Deep learning based recommender systems | Examples for building recommendation systems using modern deep learning approaches like two-tower models. |
| Classic ML | Examples for traditional machine learning tasks including XGBoost model training and time series forecasting. |
| Multi-GPU distributed training | Examples for scaling training across multiple GPUs and nodes using the Serverless GPU API. |