SpeechLLM API#

Model Classes#

class nemo.collections.nlp.models.language_modeling.megatron_base_model.MegatronBaseModel(*args: Any, **kwargs: Any)

Bases: NLPModel

Megatron base class. All NeMo Megatron models inherit from this class.

  • Initialize the model parallel world for nemo.

  • Turn on all of the nvidia optimizations.

  • If cfg.tokenizer is available, it loads the tokenizer and pad the vocab to the correct size for tensor model parallelism.

  • If using distributed optimizer, configure to be compatible with O2 level optimizations and/or model parallelism.

  • Perform gradient clipping: grad_clip_pl_default triggers the PyTorch Lightning default implementation, with_distributed_adam triggers the distributed optimizer’s implementation, megatron_amp_O2 triggers gradient clipping on the main grads, and otherwise gradient clipping is performed on the model grads.

__init__(
cfg: omegaconf.dictconfig.DictConfig,
trainer: lightning.pytorch.trainer.trainer.Trainer,
no_lm_init=True,
)

Base class from which all NeMo models should inherit

Parameters:

  • cfg (DictConfig) –

    configuration object. The cfg object should have (optionally) the following sub-configs:

    • train_ds - to instantiate training dataset

    • validation_ds - to instantiate validation dataset

    • test_ds - to instantiate testing dataset

    • optim - to instantiate optimizer with learning rate scheduler

  • trainer (Optional) – Pytorch Lightning Trainer instance

Modules#

Dataset Classes#

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