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Fix issue loading ASR pipelines #42970

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Fix issue loading ASR pipelines #42970

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Fix issue loading ASR pipeline
pcuenca Dec 20, 2025
5d86e32
ruff
pcuenca Dec 20, 2025
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5 changes: 3 additions & 2 deletions src/transformers/pipelines/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -989,9 +989,10 @@ def pipeline(
feature_extractor, _from_pipeline=task, **hub_kwargs, **model_kwargs
)

feature_extractor_type = feature_extractor.to_dict().get("feature_extractor_type", None)
if (
feature_extractor._processor_class
and feature_extractor._processor_class.endswith("WithLM")
feature_extractor_type
and feature_extractor_type.endswith("WithLM")
Comment on lines +992 to +995
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@zucchini-nlp zucchini-nlp Dec 22, 2025

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I think the feature extractor is a simple Wav2Vec2FeatureExtractor so this might not work. I found only one processor with LM in hte codebase tbh

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@pcuenca pcuenca Dec 22, 2025

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Yeah, that was my question too, I wasn't sure how many cases would be impacted. Closing this in favor of yours then.

and isinstance(model_name, str)
):
try:
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8 changes: 3 additions & 5 deletions src/transformers/pipelines/automatic_speech_recognition.py
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Expand Up @@ -193,16 +193,14 @@ def __init__(
device: Union[int, "torch.device"] | None = None,
**kwargs,
):
feature_extractor_type = feature_extractor.to_dict().get("feature_extractor_type", None)

# set the model type so we can check we have the right pre- and post-processing parameters
if model.config.model_type == "whisper":
self.type = "seq2seq_whisper"
elif model.__class__.__name__ in MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES.values():
self.type = "seq2seq"
elif (
feature_extractor._processor_class
and feature_extractor._processor_class.endswith("WithLM")
and decoder is not None
):
elif feature_extractor_type and feature_extractor_type.endswith("WithLM") and decoder is not None:
self.decoder = decoder
self.type = "ctc_with_lm"
else:
Expand Down