So I feel that this is the best feature of DLS, especially again for non-expert users like me.
After training and deploying a sentiment classifier I had a small question I want to ask. This might or might not fall within the remit of this forum so I apologize in advance.
Is it possible, through the automatic deployment interface, to allow for text as input to a deployed sentiment classifier? Right now, since the input text to the model is tokenized and passed as an numpy array, a user would need to input a series of integers separated by a ‘;’ to get a prediction. How could we go about allowing a user to simply type a sentence to the rest API? Probably that would require an additional step with a tokenizer transforming the text into appropriate integers, correct? Is that possible through DLS atm, even if we have to ‘hack’ the deployment code a bit? Or would it be simpler to add another layer smh that does this decoding before the user inputs that to DLS?
Thanks in advance!