Model Deployment Overview
In addition to Test Inference, a deploy function is available to perform inference on models created with VARISTA.
Deploying allows you to do the following
- Fast form inference
- Fast batch inference
- Inference via API
With any project open, do the following
Sidebar › Deploy
Once the deployment is done, it will appear in the deployment list.
Objects that are in the process of being deployed will have an orange indicator, which will change to a green check mark when complete.
To deploy a model, with any project open, do the following
Sidebar › Modeling › Any model › (top right of screen) Deploy
A dialog box for setting the deployment name will appear, so set an arbitrary name.
The number of deployments that can be created depends on the plan, so please check the Pricing Page for details.
After setting the name and selecting OK, it will appear in the Deploy list.
When the deployment is completed, the following functions will be available.
You can see the user who did the deployment, the date and time, the status, the model information, and stop and resume the deployment.
This function allows you to upload files and perform inference continuously, similar to test prediction. Up to 10 files can be uploaded at a time.
- Number of simultaneous uploads: 10 files
- Supported files: csv, tsv, xls, xlsx
- File size: 1024MB / file
After deploying the model, a URL will be issued, and you can send a request to this URL using the POST method to perform inference.
- API URL: The URL of the API. It cannot be changed.
- API Key: Key information to be used when authenticating the API URL.
- Project ID: The project ID.
- Sample Script: A sample script for making a request in Python.