triton-inference-server
CommunityDeploy and scale production-ready ML models efficiently with NVIDIA Triton.
Authorhung-phan
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps with the efficient deployment and scaling of ML models at production scale, solving issues like concurrency, batching, multiple frameworks support, and model orchestration.
Core Features & Use Cases
- Multi-model serving: Serve multiple models, including different frameworks, from the same infrastructure.
- Dynamic batching: Automatically batches requests to maximize GPU utilization and throughput.
- Concurrent model execution: Runs multiple instances of the same or different models simultaneously.
- Ensemble and BLS: Supports declarative pipelines and imperative Python-based business logic scripting for complex model workflows.
- Use Case: Use Triton Inference Server to deploy a model pipeline for an online chatbot that performs text classification and response generation, optimizing performance and resource usage.
Quick Start
Deploy the Triton Inference Server with the tritonserver command and point to the model repository with --model-repository=/path/to/models.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 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: triton-inference-server Download link: https://github.com/hung-phan/ml-skills/archive/main.zip#triton-inference-server Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
Agent Skills Search Helper
Install a tiny helper to your Agent, search and equip skill from 620,000+ vetted skills library on demand.