Guide for users
Last updated
Last updated
Multi AI platform lets you run machine learning models with a cloud API, without having to understand the intricacies of machine learning or manage your own infrastructure. You can run open-source models that other people have published, or package and publish your own models. Those models can be public or private.
Let's start by defining some important terms that you'll need to know:
Models: In the world of machine learning, the word "model" can mean many different things depending on context. It can be the source code, the trained weights, the architecture, or some combination thereof. At Multi AI, when we say "model" we're generally referring to a trained, packaged, and published software program that accepts inputs and returns outputs.
Versions: Just like normal software, machine learning models change and improve over time, and those changes are released as new versions. Whenever a model author retrains a model with new data, fixes a bug in the source code, or updates a dependency, those changes can influence the behavior of the model. The changes are published as new versions, so model authors can make improvements without disrupting the experience for people using older versions of the model. Versioning is essential to making machine learning reproducible: it helps guarantee that a model will behave consistently regardless of when or where it's being run.
We are using a hold-to-use model as an interim solution since the oracle and pay-per-use model have not been implemented yet. The requirements are set in MAI tokens and are not correlated with the dollar price, so we consider it a rational decision to adjust these requirements based on market cap.
In the table above, you can see the key milestones that will influence the holding requirements for using AI models.
Changes can occur in both directions and depend on what happens first. We believe that as the project grows, the requirements should be lowered to increase the potential number of users and reduce the entry barrier to an acceptable level.
You can run models on Multi AI platform using the web or the cloud API (soon).
The web interface is a good place to start when trying out a model for the first time. It gives you a visual view of all the inputs to the model, and generates a form for running the model right from your browser:
