Hi, I am new here and I have been reading about Gradient today. Basically, up to now, I would spin-up my VM, launch a jupyter notebook, open the notebook in the browser and work.
There are some disadvantages to this, however. The time you spend coding is uptime (i.e. paid time). I want to make sure I got this correctly:
Gradient is a CLI module that allows you to only send execution commands to an ad-hoc VM (jobs). For example if I write code to train a neural network in a notebook, I can then send just the train method through Gradient and I only pay for the time the network actually trains (time the job takes to run) and not for the entire time I spend coding. Is this correct?
I can recover trained models (saved) and training history after the job is finished?
Can I monitor the net’s training with Tensorboard?
What is the job limit with various subscriptions? Does 10 jobs/month means I can only train my model (or run some script) 10 times per month?
Finally, is there a fully-worked example of training a network using Gradient and how to then recover your model?