“Training” refers to a process where training data is passed backwards through a model in order to modify the model’s weights. This happens before the model is deployed to the public. Search happens at (or right before) inference time (i.e. when the model is actually used) and does not modify the model weights.
“Training” refers to a process where training data is passed backwards through a model in order to modify the model’s weights. This happens before the model is deployed to the public. Search happens at (or right before) inference time (i.e. when the model is actually used) and does not modify the model weights.