--- title: Registering a Model to vLLM --- [](){ #new-model-registration } vLLM relies on a model registry to determine how to run each model. A list of pre-registered architectures can be found [here][supported-models]. If your model is not on this list, you must register it to vLLM. This page provides detailed instructions on how to do so. ## Built-in models To add a model directly to the vLLM library, start by forking our [GitHub repository](https://github.com/vllm-project/vllm) and then [build it from source][build-from-source]. This gives you the ability to modify the codebase and test your model. After you have implemented your model (see [tutorial][new-model-basic]), put it into the directory. Then, add your model class to `_VLLM_MODELS` in so that it is automatically registered upon importing vLLM. Finally, update our [list of supported models][supported-models] to promote your model! !!! important The list of models in each section should be maintained in alphabetical order. ## Out-of-tree models You can load an external model [using a plugin][plugin-system] without modifying the vLLM codebase. To register the model, use the following code: ```python # The entrypoint of your plugin def register(): from vllm import ModelRegistry from your_code import YourModelForCausalLM ModelRegistry.register_model("YourModelForCausalLM", YourModelForCausalLM) ``` If your model imports modules that initialize CUDA, consider lazy-importing it to avoid errors like `RuntimeError: Cannot re-initialize CUDA in forked subprocess`: ```python # The entrypoint of your plugin def register(): from vllm import ModelRegistry ModelRegistry.register_model( "YourModelForCausalLM", "your_code:YourModelForCausalLM" ) ``` !!! important If your model is a multimodal model, ensure the model class implements the [SupportsMultiModal][vllm.model_executor.models.interfaces.SupportsMultiModal] interface. Read more about that [here][supports-multimodal].