ScriptAI Infrastructurev1.0

Model Serving (vLLM)

by AaaS · free · Last verified 2026-03-01

This script automates the deployment of a large language model using the vLLM inference engine. It creates a high-throughput, OpenAI-compatible API endpoint. Key features like PagedAttention and continuous batching are configured to maximize performance and memory efficiency, making it suitable for production environments.

https://aaas.blog/script/model-serving-vllm ↗

C+

C+—Average

Adoption: BQuality: AFreshness: ACitations: BEngagement: F

Specifications

License: MIT
Pricing: free
Capabilities: High-throughput LLM inference, OpenAI-compatible API endpoint creation, PagedAttention for efficient memory management, Continuous batching for increased server utilization, Tensor parallelism for multi-GPU inference, Support for a wide range of Hugging Face models, Health and metrics monitoring endpoints, Streaming output for token-by-token generation, Automated model downloading and caching, Configurable quantization support (e.g., AWQ)
Integrations: [object Object], [object Object], [object Object], [object Object], [object Object]
Use Cases: [object Object], [object Object], [object Object], [object Object], [object Object]
API Available: No
Language: python
Dependencies: vllm, torch, uvicorn, fastapi, prometheus-client
Environment: Python 3.11+ with CUDA 12 and Docker
Est. Runtime: 2-5 minutes for setup; server runs continuously
Tags: llm-serving, model-deployment, vllm, inference-optimization, openai-api, paged-attention, continuous-batching, tensor-parallelism, mlops, gpu-inference, automation
Added: 2026-03-17
Completeness: 0.7%

Index Score

58.6

Adoption

Quality

Freshness

Citations

Engagement

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