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

# Deploy Fine-Tuned model

After training the model, you can deploy the LoRA Model with Simplismart

To deploy your fine-tuned model, follow the detailed steps outlined below, which guide you through the process of optimizing, configuring, and completing the deployment to make your model ready for use.

### **Merge with Base Model**

Click on **Compile** to merge the LoRA adapter back into the base model, creating a fine-tuned model. This step will take you to the [**Add Model**](/model-suite/optimise-a-model) page. Follow the next steps to create an optimised version of the model ready to be deployed via the Simplismart Model Suite.

<img src="https://mintcdn.com/simplismart-3f10d72e/gTRCmRuan7ftye2b/images/VLM_deploy.png?fit=max&auto=format&n=gTRCmRuan7ftye2b&q=85&s=7d9d3114bab30cefce04bfae69ed5b29" alt="title" width="2000" height="1128" data-path="images/VLM_deploy.png" />

***

### **Optimize the Fine-Tuned Model**

While compiling the LoRA with the base model, you will have the option to optimize the model for deployment.

***

### **Enter Model Details**

Provide the name for your fine-tuned model.

<img src="https://mintcdn.com/simplismart-3f10d72e/gTRCmRuan7ftye2b/images/VLM_Deploy_2.webp?fit=max&auto=format&n=gTRCmRuan7ftye2b&q=85&s=516c0eca5560766fa2bd8d28345d9bf8" alt="title" width="2304" height="1250" data-path="images/VLM_Deploy_2.webp" />

***

### **Select Optimizing Infrastructure**

Choose the right optimization infrastructure for the model based on the size of the base model, specifically the GPU RAM required to run the model for a given quantization.

<Note>
  For example, a **Llama 3.1 8B** model can run on a **T4 GPU** with a **4-bit quantization** but may run into **CUDA OOM errors** with an **FP16 quantization**.
</Note>

<img src="https://mintcdn.com/simplismart-3f10d72e/gTRCmRuan7ftye2b/images/VLM_Deploy_3.webp?fit=max&auto=format&n=gTRCmRuan7ftye2b&q=85&s=65f1a260eb923de4739150cf5b5dac15" alt="title" width="2304" height="1196" data-path="images/VLM_Deploy_3.webp" />

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### **Update Optimization Configuration**

Modify the optimization settings as needed, and select the desired quantization for your optimised model. If unsure about the rest of the optimization configuration, leave it at the default values.

<Note>
  Please refrain from changing the **model configuration** in this step.
</Note>

***

### **Add the Model**

Click **Add Model** to save your fine-tuned model to the [**My Models**](https://app.simplismart.ai/my-models) section.

***

### **Deploy the Model**

Once the model has been successfully optimised and saved to your repository, you can deploy it via the Simplismart Model Suite. You can refer to the deployment steps [here](/model-suite/deployments/creating-a-deployment).