AI Models repository
Dernière mise à jour
Dernière mise à jour
For each AI system you register, you'll need to enter the AI model(s) used.
An artificial intelligence model can be defined as a computer program designed to perform specific tasks using machine learning and data analysis techniques. Here's a more detailed definition:
Foundations : An AI model is based on specific algorithms and architectures (such as neural networks for deep learning) that enable learning from data.
Learning: This is trained by processing large data sets to identify patterns and relationships.This enables the model to make predictions or generate content based on the new data it receives.
Functionality: This is the purpose for which the model is used.For example: image generation for the MidJourney model.
Use: These models are deployed in a wide range of applications, from chatbots and virtual assistants to data analysis and content creation, providing advanced, automated solutions in a variety of fields.
To create a repository, go to the "AI Models" tab.
Then click on the "Create an AI model" button. A window opens in which you can enter the required information.
Don't be afraid to go into great detail in the description section, adding the features and information you have on the model.
You will also need to select its training type. The learning type of an AI model refers to the method by which the model is trained to perform its tasks. Each type is adapted to specific applications and influences the way the model generalizes the knowledge acquired. There are 4 of them, and you'll find a definition next to each one to help you choose.
To link an AI system to a model, go to the AI system concerned. In the second section, entitled "AI Models", you'll find a selector from which you can choose one or more models from those you have saved in your model repository.
elect the models concerned, then fill in the "description of use" field. This explains how the model is used in the AI system concerned.
