An instance is a virtual machine that you can set up and configure via Segmind. You can connect to an Instance via JupyterLab or VS Code interfaces (IDEs).
Configure | Comments |
Name | Tweet Sentiment Extraction |
Environment | Select an environment. Eg. Tensorflow 2.2.2, PyTorch 1.4, LightGBM, XGBoost. You can add custom packages once you have started the instances. |
Size | Select the CPU, Memory, and GPU from available templates. You can change this anytime later. |
IDE | Select an interface also called Integrated Development Environment. Choose between JupyterLab and VS Code. |
Storage | Storage attached to the instance. Shutting down instances will retain the storage. Deleting instances will delete the storage |
Project | Connect a project to track its activities and costs. |
Datastore | Select a datastore to connect to. Learn more about Datastore here. |
Spot | Select this to run the instance on spot mode. Instances that can be terminated at any time without notice. Spot instances are much cheaper (~ 50%) than normal instances and can be used to run non-critical workloads. |
To stop an instance, click on the "Stop Notebook" button found under the settings tab on an instance page. Once you stop an instance, you won't be charged for the instance.
You can restart an instance from the /dashboard or /instances page. Click on the "Start Notebook" button to get back into an instance. You can specify the Size and IDE while restarting an instance.
Move between any instance to scale up or down depending on your compute and memory requirements. To know more about available sizes, check out our pricing page.
You can delete an instance from the settings menu on the right side of the Instance page. Remember that you will lose access to the environment you created and the data stored on the instance permanently when you delete the instance.