nemo_automodel.components.models.qwen3_omni_moe.state_dict_adapter

Module Contents

Classes

Name	Description
`Qwen3OmniMoeStateDictAdapter`	Converts between HF Qwen3OmniMoe checkpoints and grouped-experts native format.

Data

logger

API

class nemo_automodel.components.models.qwen3_omni_moe.state_dict_adapter.Qwen3OmniMoeStateDictAdapter(
    config: typing.Any,
    moe_config: nemo_automodel.components.moe.config.MoEConfig,
    backend: nemo_automodel.components.models.common.BackendConfig,
    dtype: torch.dtype = torch.float32
)

Bases: MoESplitExpertsStateDictMixin, StateDictAdapter

Converts between HF Qwen3OmniMoe checkpoints and grouped-experts native format.

nemo_automodel.components.models.qwen3_omni_moe.state_dict_adapter.Qwen3OmniMoeStateDictAdapter.convert_single_tensor_to_hf(
    fqn: str,
    tensor: typing.Any,
    kwargs = {}
) -> list[tuple[str, typing.Any]]

nemo_automodel.components.models.qwen3_omni_moe.state_dict_adapter.Qwen3OmniMoeStateDictAdapter.from_hf(
    hf_state_dict: dict[str, typing.Any],
    device_mesh: typing.Optional[torch.distributed.device_mesh.DeviceMesh] = None,
    kwargs = {}
) -> dict[str, typing.Any]

nemo_automodel.components.models.qwen3_omni_moe.state_dict_adapter.Qwen3OmniMoeStateDictAdapter.to_hf(
    state_dict: dict[str, typing.Any],
    exclude_key_regex: typing.Optional[str] = None,
    quantization: bool = False,
    kwargs = {}
) -> dict[str, typing.Any]

nemo_automodel.components.models.qwen3_omni_moe.state_dict_adapter.logger = logging.getLogger(__name__)