This repository provides reference examples for training and deploying machine learning models at scale using the MosaicML platform. It caters to users seeking to reproduce cost estimates, understand end-to-end platform usage, deploy models, or integrate with third-party distributed training libraries. The primary benefit is providing easily forkable and modifiable code to accelerate adoption of the MosaicML ecosystem.

How It Works

The examples are categorized into four types: benchmarks for cost estimate reproduction, end-to-end examples covering the full platform lifecycle, inference-deployment examples for model serving, and third-party examples showcasing integration with external distributed training tools. Each category offers specific instructions and code to demonstrate MosaicML platform capabilities.

Quick Start & Requirements

To run linting and tests for a specific subdirectory (e.g., benchmarks/bert), use the provided scripts: bash ./scripts/lint_subdirectory.sh <subdirectory> bash ./scripts/test_subdirectory.sh <subdirectory>

Further setup details and platform usage instructions are available within the README of each example subdirectory.

Highlighted Details

• Reference examples for reproducing MosaicML blog cost estimates.
• End-to-end workflows from data processing to model deployment.
• Model handler and deployment YAMLs for MosaicML inference.
• Integration examples with third-party distributed training libraries.

Maintenance & Community

This repository is part of the MosaicML ecosystem. For community engagement and platform information, refer to:

• MosaicML platform sign up: https://www.mosaicml.com/
• MosaicML docs: https://docs.mosaicml.com/
• MosaicML blog: https://www.mosaicml.com/blog/

Licensing & Compatibility

The repository's licensing is not explicitly stated in the provided README. Users should verify licensing terms for commercial use or integration with closed-source projects.

Limitations & Caveats

The README does not specify installation instructions beyond running provided scripts for testing/linting specific subdirectories. Users will need to consult individual example READMEs for detailed setup and dependency requirements.