| """ | |
| Pico Config Package | |
| The modules of this package are where you can specify the hyperparameters for the Pico model, | |
| the dataset, the training process, evaluation, etc. | |
| As with anything else in Pico, we've designed for the configuration setup to be as flexible | |
| as possible. By default the configs are implemented as vanilla dataclasses -- this makes it easy to | |
| switch to different config management systems if you want, like hydra. | |
| Some things to NOTE: | |
| - All hyperparameters are initialized with default values, which can be overridden. | |
| - The default vocab size is set to the size of the OLMo tokenizer. | |
| """ | |
| # For convenience, we export the config classes here | |
| from .checkpointing_config import CheckpointingConfig | |
| from .data_config import DataConfig | |
| from .evaluation_config import EvaluationConfig | |
| from .model_config import ModelConfig | |
| from .monitoring_config import MonitoringConfig | |
| from .training_config import TrainingConfig | |
| __all__ = [ | |
| "CheckpointingConfig", | |
| "DataConfig", | |
| "EvaluationConfig", | |
| "ModelConfig", | |
| "MonitoringConfig", | |
| "TrainingConfig", | |
| ] | |