WarpGBM
Train GPU-accelerated gradient boosting models as a stateless cloud service, enabling fast predictions and portable artifact export for AI agents and developers.
关于
WarpGBM is a cloud service designed to outsource gradient boosting decision tree (GBDT) workloads, providing AI agents and developers instant access to GPU-accelerated machine learning. Built upon the high-performance WarpGBM library, this service handles model training on NVIDIA A10G GPUs, delivers portable model artifacts, and features smart 5-minute caching for sub-100ms inference, making it ideal for rapid prototyping and deployment without managing complex infrastructure.
主要功能
- Multi-Model support (WarpGBM GPU and LightGBM CPU)
- Smart caching for sub-100ms inference using artifact_id
- Export portable joblib model artifacts for use anywhere
- Native integration with Model Context Protocol (MCP) for AI agents
- Stateless architecture ensures no data storage and user ownership of models
- 1 GitHub stars
使用案例
- Conducting quick experiments and prototyping with gradient boosting models.
- Integrating GPU-accelerated gradient boosting capabilities into AI agent workflows.
- Deploying machine learning models with fast, cached inference without requiring local GPU infrastructure.
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