Signed-off-by: samithuang <285365963@qq.com> Signed-off-by: Samit <285365963@qq.com> Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
36 lines
854 B
Markdown
36 lines
854 B
Markdown
# Quickstart
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This guide will help you quickly get started with vLLM-Omni to perform:
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- Offline batched inference
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- Online serving using OpenAI-compatible server
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## Prerequisites
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- OS: Linux
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- Python: 3.12
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## Installation
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Please refer to [installation](installation/README.md)
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## Offline Inference
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Text-to-image generation quickstart with vLLM-Omni:
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```python
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from vllm_omni.entrypoints.omni import Omni
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if __name__ == "__main__":
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omni = Omni(model="Tongyi-MAI/Z-Image-Turbo")
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prompt = "a cup of coffee on the table"
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images = omni.generate(prompt)
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images[0].save("coffee.png")
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```
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For more usages, please refer to [offline inference](../user_guide/examples/offline_inference/qwen2_5_omni.md)
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## Online Serving with OpenAI-Completions API
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Please refer to [online serving](../user_guide/examples/online_serving/qwen2_5_omni.md)
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