Fine-tuning

Fine-tuning involves further training an existing LLM on a specific dataset or for a particular task. This process allows the model to adapt its knowledge and capabilities to better suit specific use cases or domains. Fine-tuning can help in:

• Improving performance on domain-specific tasks
• Reducing biases or unwanted behaviors
• Customizing the model's style or tone
• Enhancing the model's ability to follow specific instructions or formats