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How to load a checkpoint and run evaluation (inference only, no training)
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Hydra configuration file structure and conventions for models, datasets, callbacks, and training
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| name | load-eval |
| description | How to load a checkpoint and run evaluation (inference only, no training) |
To evaluate a trained model without training, pass train=False to src/train.py along with a path to the checkpoint(s).
uv run python src/train.py --config-name=train_your_project \
train=False \
paths.restore_ckpts=["./logs/train/runs/2025-01-01_00-00-00/checkpoints/last.ckpt"]
uv run python src/train.py --config-name=train_your_project \
train=False \
paths.restore_dir=./logs/train/runs/2025-01-01_00-00-00/checkpoints
All .ckpt files in the directory will be evaluated in sequence.
train=False skips the training loop and goes straight to validation.paths.restore_ckpts takes precedence over paths.restore_dir if both are set.logs/ structure as a training run (metrics, visualizations, etc.).Both restore_ckpts and restore_dir default to null (defined in configs/paths/default.yaml). Override them on the command line as shown above, or set them in configs/train_your_project.yaml for repeated use:
train: False
paths:
restore_dir: ./logs/train/runs/2025-01-01_00-00-00/checkpoints