0 Fork 0

Files

T

SamitandHongsheng Liu 4ac3e6e7d0 [Docs] Add basic usage examples for diffusion (#222 )

Signed-off-by: samithuang <285365963@qq.com>
Signed-off-by: Samit <285365963@qq.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>

2025-12-08 00:00:25 -08:00

854 B

Raw Blame History

Quickstart

This guide will help you quickly get started with vLLM-Omni to perform:

Offline batched inference
Online serving using OpenAI-compatible server

Prerequisites

OS: Linux
Python: 3.12

Installation

Please refer to installation

Offline Inference

Text-to-image generation quickstart with vLLM-Omni:

from vllm_omni.entrypoints.omni import Omni

if __name__ == "__main__":
    omni = Omni(model="Tongyi-MAI/Z-Image-Turbo")
    prompt = "a cup of coffee on the table"
    images = omni.generate(prompt)
    images[0].save("coffee.png")

For more usages, please refer to offline inference

Online Serving with OpenAI-Completions API

Please refer to online serving

854 B Raw Blame History