Do generative model produce varying outputs for same input I am new to data sciences. I believe the generative model generate responses on-the-fly for a valid user input. Is it correct to assume that such models would generate different responses for the same question?
For e.g: if we trained the model on say medical data. Now if user 1 asked &quot;what is fever&quot; and user 2 asked the same question, could be that user 1 and 2 will receive different answers? if this is so then how to circumvent this problem?
thanks in advance
This depends entirely on the specific model. There are generative models, like most Generative Adversarial Networks (GANs) that receive a random number and generate data. There are other generative models that generate a probability distribution over the output space (e.g. text generation models), and therefore whether the model generates data deterministically depends on the inference procedure (e.g. greedy, sampling, beam search).
If you want your model to generate outputs deterministically, you just select a model and inference method that assures that.
In your example, you may have a normal seq2seq model (e.g. Transformer) and use beam search for decoding, and the outputs will be the same given the same input.