> For the complete documentation index, see [llms.txt](https://genai-studio.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://genai-studio.gitbook.io/docs/getting-started/feature-overview/fine-tuning.md).

# Fine-tuning

## **Overview**

This screenshot showcases the interface for fine-tuning models within the Edge AI SDK. Fine-tuning is a technique used to optimize pre-trained models for specific tasks. By fine-tuning, you can improve the accuracy and performance of a model in a particular application using a smaller dataset.

<figure><img src="/files/uQIzPi3JgznbGP5wIjzu" alt=""><figcaption></figcaption></figure>

## **Key Features**

The interface provides three main fine-tuning options:

* <mark style="color:blue;">**Text-to-Text (Full Parameter)**</mark>**:** Finetune popular text-to-text models using full parameter adjustment. This method involves updating all parameters in the model, typically achieving the highest accuracy but requiring more computational resources and data. (Phison AI SSD required)
* <mark style="color:blue;">**Text-to-Text (LoRA)**</mark>**:** Finetune popular text-to-text models using LoRA (Low-Rank Adaptation). LoRA is a more efficient fine-tuning method that freezes the original weights of the pre-trained model and only trains a small number of additional parameters. This significantly reduces computational and memory requirements.
* <mark style="color:blue;">**Text-to-Image**</mark>**:** Finetune popular text-to-image models. This option allows you to customize the output of text-to-image models for specific needs. This feature is under development and will be available in a future release.

## **Usage**

Users can select the appropriate fine-tuning option based on their specific task and resources.

* For the highest possible accuracy when a Phison AI SSD is attached, use "Text-to-Text (Full Parameter).
* If computational resources are limited, or a more efficient fine-tuning process is desired, "Text-to-Text (LoRA)" can be used.
* If there is a need to customize the output of text-to-image models, "Text-to-Image" can be used.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://genai-studio.gitbook.io/docs/getting-started/feature-overview/fine-tuning.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.