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databricks-model-serving

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Deploy and query Databricks model endpoints.

Data & Analytics#deploy#endpoints#mlflow#databricks#unity-catalog#model-serving#genai
Authordatasciencemonkey
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Deploy and query Databricks Model Serving endpoints for ML models and AI agents.

Core Features & Use Cases

  • Deploy traditional ML models (sklearn, xgboost) and custom PyFunc models to scalable endpoints
  • Query responses via OpenAI-compatible interfaces and Databricks REST endpoints
  • Integrate Unity Catalog Functions and Vector Search tools as endpoint capabilities

Quick Start

Log a model with MLflow and deploy it to a Databricks endpoint, then start querying it.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: databricks-model-serving
Download link: https://github.com/datasciencemonkey/coding-agents-databricks-apps/archive/main.zip#databricks-model-serving

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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