vLLM
vLLM is a fast and easy-to-use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions …
vLLM - vLLM - vLLM 文档 - docs.vllm.com.cn
vLLM 是一个用于 LLM 推理和服务的快速易用库。 vLLM 最初由加州大学伯克利分校的 天空计算实验室 开发，现已发展成为一个由学术界和工业界共同贡献的社区驱动项目。
GitHub - vllm-project/vllm: A high-throughput and memory-efficient ...
May 24, 2023 · vLLM is a fast and easy-to-use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven …
Welcome to vLLM — vLLM - docs.vllm.ai
vLLM is a fast and easy-to-use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions …
vLLM - Hugging Face
vLLM has wide support for large language models and embedding models. We recommend reading the supported models section in the vLLM documentation for a full list. vLLM also supports model …
Welcome to vLLM! — vLLM
Welcome to vLLM! vLLM is a fast and easy-to-use library for LLM inference and serving. vLLM Meetups. 1. Set up the base vLLM model. 2. Register input mappers. 3. Register maximum number of …
vllm/docs/getting_started/quickstart.md at main - GitHub
To run vLLM on Google TPUs, you need to install the `vllm-tpu` package. For more detailed instructions, including Docker, installing from source, and troubleshooting, please refer to the [vLLM on TPU …
Quickstart — vLLM - Read the Docs
The vLLM server is designed to support the OpenAI Chat API, allowing you to engage in dynamic conversations with the model. The chat interface is a more interactive way to communicate with the …
Welcome to vLLM! — vLLM
vLLM is flexible and easy to use with: Support NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs and GPUs, PowerPC CPUs, TPU, and AWS Trainium and Inferentia Accelerators. For more information, …
Serving LLMs with vLLM: A practical inference guide
5 days ago · This guide teaches the essentials of serving large language models with vLLM. It builds from foundational neural network concepts, like transformers and attention, to introduce practical …