Saving and Loading

This page covers the low-level MinT checkpoint primitives. For end-to-end operational workflows, see the dedicated Advanced Checkpoint pages.

Save for inference

sampler_path = training_client.save_weights_for_sampler(name="0000").result().path

Use this when you want a weights-only checkpoint for sampling or export.

Save for training resume

resume_path = training_client.save_state(name="0010").result().path

Use this when you want to preserve both weights and optimizer state.

Load a saved checkpoint

training_client.load_state_with_optimizer(resume_path).result()
training_client.load_state(resume_path).result()

load_state_with_optimizer(...) restores weights and optimizer state
load_state(...) restores weights only

Loss Functions Downloading Weights