vertebrae.extractors.huggingface_audio
Optional Hugging Face audio embedding extractor.
Classes
Hugging Face audio backbone extractor with explicit pooling. |
Module Contents
- class vertebrae.extractors.huggingface_audio.HFAudioExtractor(name, model_id, processor_id=None, pooling='mean', hidden_layer=None, outputs=None, structured_outputs=None, batch_size=16, sampling_rate=None, device=None, revision=None, trust_remote_code=False, processor_kwargs=None, model_kwargs=None, checkpoint_paths=None, feature_mask_fn=None, cache_identity=None)[source]
Hugging Face audio backbone extractor with explicit pooling.
- Parameters:
name (str) – User-facing extractor name.
model_id (str) – Hugging Face model identifier or local path.
processor_id (Optional[str]) – Optional Hugging Face processor identifier or local path. Defaults to model_id.
pooling (str) – Pooling mode: “mean”, “cls”, or “pooler”.
hidden_layer (Optional[int]) – Optional hidden-state layer index to pool from. Defaults to the model’s final output.
batch_size (int) – Number of audio clips encoded per batch.
sampling_rate (Optional[int]) – Default sampling rate for array inputs.
device (Optional[str]) – Optional device string.
revision (Optional[str]) – Optional model revision.
trust_remote_code (bool) – Whether to allow remote model code.
processor_kwargs (Optional[Dict[str, Any]]) – Extra keyword arguments for the processor.
model_kwargs (Optional[Dict[str, Any]]) – Extra keyword arguments for AutoModel.
outputs (Optional[List[Dict[str, Any]]])
structured_outputs (Optional[List[Dict[str, Any]]])
checkpoint_paths (Optional[List[str]])
feature_mask_fn (Optional[Callable[[int, Any], Any]])
cache_identity (Optional[str])
- fit(X, y=None)[source]
No-op fit for frozen Hugging Face audio models.
- Parameters:
X (Any)
y (Any)
- Return type:
- transform(X)[source]
Encode audio inputs into dense embeddings.
- Parameters:
X (Any)
- Return type:
numpy.ndarray