vllm/docs/serving/offline_inference.md

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Offline Inference

{ #offline-inference }

You can run vLLM in your own code on a list of prompts.

The offline API is based on the [LLM][vllm.LLM] class. To initialize the vLLM engine, create a new instance of LLM and specify the model to run.

For example, the following code downloads the facebook/opt-125m model from HuggingFace and runs it in vLLM using the default configuration.

from vllm import LLM

llm = LLM(model="facebook/opt-125m")

After initializing the LLM instance, you can perform model inference using various APIs. The available APIs depend on the type of model that is being run:

• [Generative models][generative-models] output logprobs which are sampled from to obtain the final output text.
• [Pooling models][pooling-models] output their hidden states directly.

Please refer to the above pages for more details about each API.

!!! info [API Reference][offline-inference-api]