vLLM Runtime
Shares tags: build, serving, vllm & tgi
AI Tool
Deploy Large Language Models in Minutes
Infrastructure-as-Code Templates for Seamless vLLM Deployments
Rapid, serverless deployments allow you to get started in just five minutes.Optimize costs and performance with dynamic batching and tailored hardware selections.Easily integrate OpenAI-compatible endpoints for your open-source LLMs.
Tags
BuildServingvLLM & TGI
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overview
What is Cerebrium vLLM Deployments?
Cerebrium vLLM Deployments offers infrastructure-as-code templates specifically designed to simplify the process of spinning up vLLM clusters. Emphasizing speed and efficiency, it enables developers and enterprises to deploy large language models effortlessly.
features
Key Features
Cerebrium vLLM Deployments is packed with powerful features designed to optimize your LLM deployment experience. From rapid setup times to advanced hardware support, we provide everything you need to succeed.
- Support for dynamic batching to enhance GPU utilization and reduce costs.
- Select from a variety of hardware options, including the latest NVIDIA H100 GPUs.
- Integration with HuggingFace models and multiple deployment recipes for advanced use cases.
use_cases
Real-World Applications
Cerebrium vLLM Deployments is tailored for developers and enterprises seeking to solve real-world challenges with large language models. Whether it's translation, content generation, or data retrieval, our platform equips you to meet your needs.
- Translation services for global communication.
- Content generation for digital marketing and storytelling.
- Advanced data retrieval for better business insights.
Frequently Asked Questions
How quickly can I deploy a vLLM cluster?
With Cerebrium, you can deploy a vLLM cluster in as little as five minutes, providing you with a production-ready environment without the need for infrastructure management.
What kind of hardware can I choose for my deployment?
You can select from a wide range of hardware options, including CPUs and the latest NVIDIA H100 GPUs, to ensure optimal performance for your specific workloads.
Is it compatible with OpenAI APIs?
Yes, Cerebrium enables the deployment of OpenAI-compatible endpoints for any open-source LLM, making it easier for developers familiar with the OpenAI ecosystem to integrate.