> ## Documentation Index
> Fetch the complete documentation index at: https://docs.nx1cloud.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Deploy a fine-tuned model

> Deploy a fine-tuned model so it can answer requests through an LLM Router.

You deploy a fine-tuned model to start using it for inferencing. NexusOne starts the model so it can answer
requests. When the model is ready, NexusOne adds it to an
[LLM Router](https://docs.nx1cloud.com/documentation/getting-started/deployment/deployment-architecture.md#tenant-modules).

## Prerequisites

Before starting this task, ensure you have the following:

* Required roles: `nx1_finetune_admin`, `nx1_finetune_user`, or `nx1_engineer`.
* A previously created training job with the `complete` status.

## Deploy a fine-tuned model

> [tab] Web portal
>
> Perform these steps to deploy a fine-tuned model:
>
> 1. Log in to NexusOne.
> 2. On the top navigation bar, hover your mouse over **AI** and then select **AutoML & AutoLLM**.
> 3. Click **Fine-tune LLMs (AutoLLM)**.
> 4. Click **Training**.
> 5. Click the three dots at the end of the row for the training job with the `complete` status.
> 6. Select **Deploy for inference**.
> 7. In the **Deployment name** field, enter a name for the deployment. Use up to 52 lowercase letters, digits,
>    or hyphens, and start and end with a letter or digit.
> 8. Optional: In the **Served model name** field, enter the model name that appears on the LLM Router. If you leave it
>    empty, then NexusOne uses the model's registered name from MLflow.
> 9. Optional: In the **GPU count** field, enter how many GPUs the model uses. If you leave it
>    empty, then NexusOne uses 1.
> 10. Optional: In the **Max model length** field, enter the most tokens the model can handle in one request.
> 11. Optional: In the **Min replicas** field, enter the fewest running copies of the model server NexusOne keeps.
> 12. Optional: In the **Max replicas** field, enter the most running copies of the model server NexusOne runs.
>     If you leave it empty, then NexusOne uses 4.
> 13. Click **Deploy**.
>
> The new deployment appears in the Inferencing table with the `deploying` status. When the model is ready, the
> status changes to `active` and NexusOne adds the model to an LLM Router. To follow the deployment, refer to
> [View an inferencing deployment](https://docs.nx1cloud.com/documentation/ai/tasks/automl/fine-tune-llm/inferencing/view-an-inferencing-deployment.md).

> [tab] REST API
>
> Use the [Deploy a fine-tuned model with vLLM](https://docs.nx1cloud.com/api-reference/endpoints/inferencing/deploy-a-fine-tuned-model-with-vllm.md)
> endpoint to deploy a fine-tuned model.

## Additional resources

For a high-level overview of inferencing and how it's used in NexusOne, refer to
[Fine-tune LLM](https://docs.nx1cloud.com/documentation/ai/overview/automl/fine-tune-llm.md#inferencing).


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