Models
Handle your models.
In Giza Plateform, a model represents a container for versions of your machine learning model. This design allows you to iterate and improve your ML model by creating new versions for it. Each model can have multiple versions, providing a robust and flexible way to manage the evolution of your ML models. This traceability feature ensures that you have a clear record of the original model used for transpilation, who performed the transpilation, and the output generated.
Remember, you need to be logged in to use these functionalities!
Create a Model
Creating a new model in Giza is a straightforward process. You only need to provide a name for the model using the --name
option. You can also add a description of the model using the --description
option. This can be helpful for keeping track of different models and their purposes.
Here's how you can do it:
Typically, the transpile
command is used to handle model creation. During this process, the filename is checked for an existing model. If none is found, a new model is automatically created. However, manual creation of a model is also supported. For more information, refer to the transpile documentation.
List Models
Giza provides a simple and efficient way to list all the models you have stored on the server. This feature is especially useful when you have multiple models and need to manage them effectively.
To list all your models, you can use the list
command. This command retrieves and displays a list of all models stored in the server. Each model's information is printed in a json format for easy readability and further processing.
Here's how you can do it:
Retrieve Model Information
You can retrieve detailed information about a model stored on the server using its unique model id. This includes its name, description, and other id:
Now we can see that we have a model successfully transpiled!
Transpile a model
Note: This is explained extensively in the transpile documentation.
Transpiling a model in Giza is a crucial step in the model deployment process as an endpoint. Transpilation is the process of converting your machine learning model into a format that can be executed on Giza. Depending the ZKML framework chosen, this process involves converting the model into a series of Cairo instructions.
When you execute the 'transpile' command, it initially checks for the presence of the model on the Giza platform. If no model is found, it automatically generates one and performs the transpilation. Here is an example of the command:
It's worth noting that if you already have created a model, you can transpile it by specifying the model ID:
This method ise useful when you intend to create a new version of an existing model.
For more information, refer to the transpile documentation.
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