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

# LoRA Fine-Tuning

> How to fine-tune LLMs within minutes using LoRA.

# What is LoRA

[LoRA, or Low-Rank Adaptation](https://blog.premai.io/slm-vs-lora-llm-edge-deployment-and-fine-tuning-compared), is a technique designed to make fine-tuning Large Language Models (LLMs) much more efficient.

In traditional fine-tuning, you have to update all the parameters of an LLM, which can be slow and resource-intensive.

With LoRA, instead of changing the entire model, you add a few small, trainable components to the base LLM. These components are trained for your specific task,
allowing the model to adapt quickly without needing to retrain everything from scratch.

## When to use LoRA

Because LoRA only updates a small part of the model, it's much faster than standard fine-tuning.
As a general rule, if regular fine-tuning of an LLM on a large dataset would take around 30 minutes,
LoRA can often get the job done in 10 minutes or less. This makes it a great choice when you want to
adapt a model quickly and efficiently, without needing deep expertise in machine learning.

Below is a table comparing when to use LoRA versus full fine-tuning:

| Scenario                               | LoRA | Full Fine-tuning | Real-world Example                                             |
| -------------------------------------- | ---- | ---------------- | -------------------------------------------------------------- |
| **Quick adaptation** 🚀                | ✅    | ❌                | Customizing a chatbot for your company's tone and style        |
| **Limited computational resources** 💻 | ✅    | ❌                | Small startup fine-tuning on a laptop or basic GPU             |
| **Small to medium datasets** 📊        | ✅    | ❌                | Training on 1,000-10,000 customer support tickets              |
| **Fast experimentation** 🧪            | ✅    | ❌                | Testing different prompt styles for marketing content          |
| **Domain-specific tasks** 🎯           | ✅    | ⚠️               | Adapting a model for legal document analysis                   |
| **Massive datasets** 📈                | ❌    | ✅                | Training on millions of medical research papers                |
| **Fundamental behavior change** 🔄     | ❌    | ✅                | Teaching a general model to code in a new programming language |
| **Maximum performance** 🏆             | ⚠️   | ✅                | Building a state-of-the-art translation system                 |
| **Budget constraints** 💰              | ✅    | ❌                | Bootstrapped companies with limited cloud computing budget     |
| **Time-sensitive projects** ⏰          | ✅    | ❌                | Launching a customer service bot in a week                     |

***

# Using LoRA in Prem Studio

<Steps>
  <Step title="Create a New Fine-Tuning Job">
    <img src="https://static.premai.io/prem-saas-docs/guides/finetuning/create-lora-finetuning.gif" alt="GIF of clicking to create a new FT Job" />

    To get started, click the **+ Create Fine-Tuning Job** button in the top right corner of the page.
    Fill in the name and select your dataset. Once you've configured these settings, click the **Create Fine-Tuning Job** button.
  </Step>

  <Step title="Configure Your LoRA Settings">
    <img src="https://static.premai.io/prem-saas-docs/guides/finetuning/enable-lora-finetuning.gif" alt="GIF of starting LoRA FT Job" />

    * Choose the model you want to fine-tune and toggle on the LoRA option.
    * Click the **Start Experiments** button.
    * A confirmation dialog will appear asking you to confirm starting the experiments.

    <Warning>
      Gemma models (specifically Gemma 3 1B and Gemma 3 4B) are not available for LoRA fine-tuning.
    </Warning>

    <Note>
      For complex tasks, you may need to increase the number of epochs to achieve the best results.
    </Note>
  </Step>
</Steps>

Once you've started the process, your LoRA fine-tuning job will complete in just a few minutes.