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fix loading of hyb ctc rnnt bpe models when using from pretrained #15042

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nithinraok merged 2 commits into from
Nov 9, 2025
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fix loading of hyb ctc rnnt bpe models when using from pretrained #15042

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fix loading of hyb ctc rnnt bpe models when using from pretrained
nithinraok Nov 7, 2025
491109c
Apply isort and black reformatting
nithinraok Nov 7, 2025
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12 changes: 11 additions & 1 deletion nemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models_prompt.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@
from nemo.collections.asr.parts.submodules.rnnt_decoding import RNNTBPEDecoding
from nemo.collections.asr.parts.utils.rnnt_utils import Hypothesis
from nemo.collections.common.data.lhotse import get_lhotse_dataloader_from_config
from nemo.core.classes.common import typecheck
from nemo.core.classes.common import PretrainedModelInfo, typecheck
from nemo.core.classes.mixins import AccessMixin
from nemo.core.neural_types import (
AcousticEncodedRepresentation,
Expand Down Expand Up @@ -1000,3 +1000,13 @@ def setup_test_data(self, test_data_config: Optional[Union[DictConfig, Dict]]):
# preserve config
self._update_dataset_config(dataset_name='test', config=test_data_config)
self._test_dl = self._setup_dataloader_from_config(config=test_data_config)

@classmethod
def list_available_models(cls) -> List[PretrainedModelInfo]:
"""
This method returns a list of pre-trained model which can be instantiated directly from NVIDIA's NGC cloud.

Returns:
List of available pre-trained models.
"""
return None
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