he trained model to the Hub --checkpointing_steps: frequency of saving a checkpoint as the model trains; this is useful if for some reason training is interrupted, you can continue training from that checkpoint by adding --resume_from_checkpoint to your training command --num_vectors: the number of vectors to learn the embeddings with; increasing this parameter helps the model learn better but it comes with increased training costs --placeholde