This repository provides a comprehensive collection of self-contained examples for building and deploying Machine Learning/AI applications on the Cerebrium Serverless GPUs platform. It targets developers and researchers looking to deploy LLMs, process voice, or handle image/video tasks, offering practical, ready-to-use code to accelerate development.

How It Works

Examples are organized by category, demonstrating specific use cases from basic deployments to advanced techniques like VLLM for inference speed and multi-GPU setups. Each example is designed for direct deployment on Cerebrium using the cerebrium deploy command after cloning the repository, simplifying the process of testing and integrating various ML models and workflows.

Quick Start & Requirements

• Install/Run: Clone the repository and run cerebrium deploy within each example folder.
• Prerequisites: Cerebrium account and CLI. Specific examples may require additional libraries or models detailed within their respective directories.
• Resources: Requires Cerebrium platform access.
• Links: Documentation, Discord Community, Slack Community

Highlighted Details

• Covers a wide range of ML tasks: LLMs, voice processing (Whisper, XTTS), image/video generation (ComfyUI, SDXL), and integrations with Langchain/Langsmith.
• Demonstrates advanced deployment strategies including VLLM for faster inference, multi-GPU setups, and WebSockets for streaming.
• Includes examples for FastAPI and Gradio for building ML web interfaces.
• Offers guidance on batching requests with LitServe, vLLM, and transformers.

Maintenance & Community

The repository encourages community contributions, offering swag for merged pull requests. Active community channels are available via Discord and Slack for support and discussion.

Licensing & Compatibility

The repository itself is not explicitly licensed in the README. Examples may contain code with varying licenses depending on the underlying libraries and models used. Users should verify compatibility for commercial or closed-source use on a per-example basis.

Limitations & Caveats

The repository focuses solely on demonstrating use cases within the Cerebrium ecosystem; examples may not be directly transferable to other platforms without modification. Specific hardware or software dependencies for individual examples are not centrally listed and must be checked within each example's documentation.