doc: improve HF-related docstring

pyannote/audio/core/pipeline.py

@@ -66,9 +66,9 @@ def expand_subfolders(
     revision : str, optional
         Revision when loading from the huggingface.co model hub.
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
     """
 
     if isinstance(config, dict):

pyannote/audio/pipelines/multilabel.py

@@ -55,9 +55,9 @@ class MultiLabelSegmentation(Pipeline):
     share_min_duration : bool, optional
         If True, `min_duration_on` and `min_duration_off` are shared among labels.
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
     inference_kwargs : dict, optional
         Keywords arguments passed to Inference.
 

pyannote/audio/pipelines/overlapped_speech_detection.py

@@ -98,9 +98,9 @@ class OverlappedSpeechDetection(Pipeline):
         Optimize precision at target recall
         Defaults to optimize precision/recall fscore
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
     inference_kwargs : dict, optional
         Keywords arguments passed to Inference.
 

pyannote/audio/pipelines/resegmentation.py

@@ -69,9 +69,9 @@ class Resegmentation(SpeakerDiarizationMixin, Pipeline):
         Defaults to {"collar": 0.0, "skip_overlap": False}. This is used in `get_metric`
         when instantiating the metric: GreedyDiarizationErrorRate(**der_variant).
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     Hyper-parameters
     ----------------

pyannote/audio/pipelines/speaker_diarization.py

@@ -87,9 +87,9 @@ class SpeakerDiarization(SpeakerDiarizationMixin, Pipeline):
         Defaults to {"collar": 0.0, "skip_overlap": False}. This is used in `get_metric`
         when instantiating the metric: GreedyDiarizationErrorRate(**der_variant).
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     Usage
     -----

pyannote/audio/pipelines/speaker_verification.py

@@ -209,9 +209,9 @@ class SpeechBrainPretrainedSpeakerEmbedding(BaseInference):
     device : torch.device, optional
         Device
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     Usage
     -----
@@ -393,9 +393,9 @@ class ONNXWeSpeakerPretrainedSpeakerEmbedding(BaseInference):
     device : torch.device, optional
         Device
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     Usage
     -----
@@ -629,9 +629,9 @@ class PyannoteAudioPretrainedSpeakerEmbedding(BaseInference):
     device : torch.device, optional
         Device
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     Usage
     -----
@@ -732,9 +732,9 @@ def PretrainedSpeakerEmbedding(
     device : torch.device, optional
         Device
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     Usage
     -----
@@ -794,9 +794,9 @@ class SpeakerEmbedding(Pipeline):
         See pyannote.audio.pipelines.utils.get_model for supported format.
         Defaults to no voice activity detection.
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     Usage
     -----

pyannote/audio/pipelines/speech_separation.py

@@ -88,9 +88,9 @@ class SpeechSeparation(SpeakerDiarizationMixin, Pipeline):
         Defaults to {"collar": 0.0, "skip_overlap": False}. This is used in `get_metric`
         when instantiating the metric: GreedyDiarizationErrorRate(**der_variant).
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     Usage
     -----

pyannote/audio/pipelines/utils/getter.py

@@ -49,9 +49,9 @@ def get_model(
         pretrained model on Huggingface.co and loads with `Model.from_pretrained(model)`
         When `dict`, loads with `Model.from_pretrained(**model)`.
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     Returns
     -------
@@ -117,9 +117,9 @@ def get_calibration(
         pretrained calibration on Huggingface.co and loads with `Calibration.from_pretrained(calibration)`.
         When `dict`, loads with `Calibration.from_pretrained(**calibration)`.
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     Returns
     -------

pyannote/audio/pipelines/voice_activity_detection.py

@@ -76,9 +76,9 @@ class VoiceActivityDetection(Pipeline):
         Optimize (precision/recall) fscore. Defaults to optimizing detection
         error rate.
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
     inference_kwargs : dict, optional
         Keywords arguments passed to Inference.
 

pyannote/audio/utils/hf_hub.py

@@ -56,9 +56,9 @@ def download_from_hf_hub(
     subfolder : str, optional
         Folder inside the model repo.
     token : str or bool, optional
-        Token to be used for the download.
+        Huggingface token to be used for downloading from Huggingface hub.
     cache_dir: Path or str, optional
-        Path to the folder where cached files are stored.
+        Path to the folder where files downloaded from Huggingface hub are stored.
 
     See also
     --------