Language Model Fine-Tuning

What is Fine Tuning?

Improve the effectiveness and accuracy of your AI by training your language model with industry- or task-specific data.

Fine tuning optimizes a pre-trained language model (LLM, Large Language Model) for specific industry or task requirements by retraining it with a targeted selection of data.

This specific adjustment significantly increases the accuracy and efficiency of the model when it comes to industry- or task-specific queries.

Customization through Fine Tuning: Your AI, Your Advantage

Stand out from the crowd with AI solutions that are as unique as your business. Evoya AI’s fine-tuning service gives you the opportunity to personalize your AI.

For SMEs, this means that your AI solutions can not only respond more precisely to your own individual needs but also to those of your customers, leading to improved performance, more effective automation, and increased customer satisfaction.

Needs Analysis and Strategy Development

The first step involves a detailed needs analysis to understand your business processes and goals. In this context, we evaluate both the potential applications of the language model in your company and the potentials and limitations of fine tuning.

Based on this information, we develop a suitable implementation strategy. We define, based on your requirements such as data protection and compliance, whether and how the language model – if not already specified – will be integrated into your existing systems (On Premise) or implemented in the cloud, depending on the need within or outside of Switzerland.

Data Preparation and Model Training

In the second step, we focus on selecting and preparing the data needed to train your language model. This includes collecting and analyzing data that reflects your industry specifics and automation requirements.

Subsequently, the actual fine tuning of the model is carried out with this data.

Deployment and Continuous Optimization

After fine tuning, the language model is integrated into your systems, either On Premise or in the cloud – within or outside of Switzerland, based on the strategy defined in Step 1.

Additionally, we provide continuous support and optimization to further improve the model’s performance over time and adapt to changing business requirements.