# Core Concepts

### **How ModelFactory Works**

ModelFactory integrates dataset access control and model fine-tuning into a seamless workflow, ensuring data security and ownership integrity. The platform’s primary processes include:

<figure><img src="/files/Sx1ZDu2P88cPp62A1tAO" alt=""><figcaption></figcaption></figure>

### **Model Selection & Configuration**

* Users select from a wide range of LLMs (e.g., LLaMA, Mistral, DeepSeek).
* Hyperparameters like learning rate, batch size, and epochs are configured through the GUI.<br>

<figure><img src="/files/gqT5vjYDrxmBVemCPnRW" alt=""><figcaption></figcaption></figure>

### **Fine-Tuning Process**

* The fine-tuning engine supports methods such as LoRA and QLoRA.
* Real-time dashboards provide training progress insights.

<figure><img src="/files/6dQ2ryUHey8z6mAc48Us" alt=""><figcaption></figcaption></figure>

### **Chat Interface**

* Enables users to interact with fine-tuned models directly through the GUI or through API.
* Supports real-time question-and-answer sessions or task-specific interactions.

<figure><img src="/files/V6z3GFjbdvUGBL5Pstaw" alt=""><figcaption></figcaption></figure>


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