I am a developer from Gradient. I think the most interesting use case of our product is interactive few-shot fine-tuning in a Jupyter Notebook. When fine-tuning a model with less than 10 samples and around 3 epoch, it can learn knowledge in a couple of seconds, then you can immediately get the fine-tuned model.

The experience is like to be your model's private tutor. It just continuously learns new things you told it, like a life.

Be cautious about your learning rate, or it will go mad.