Pyannote/speaker-diarization - [WinError 1314] A required privilege is not held by the client
Hi,I’m trying to use pyannote/speaker-diarization on a set of audiofile interview with two speakers. My goal is to identify who speaks when and transcript it in a text.To do so I installed pyannote following the instruction found onpyannote githubin a new conda environnement.I first use anaconda prompt to login with the commandhuggingface-cli loginand then I enter my token and get a validation.After I run the code foundherefrom pyannote.audio import Pipelinepipeline = Pipeline.from_pretrained(“pyannote/speaker-diarization”,use_auth_token=True)And I get the error :OSError                                   Traceback (most recent call last)Cell In[22], line 1----> 1 pipeline = Pipeline.from_pretrained(“pyannote/speaker-diarization”,2                                     use_auth_token=True3                                    )File ~\Anaconda3\envs\Alex\envs\pyannote\lib\site-packages\pyannote\audio\core\pipeline.py:129, in Pipeline.from_pretrained(cls, checkpoint_path, hparams_file, use_auth_token, cache_dir)127 params = config[“pipeline”].get(“params”, {})128 params.setdefault(“use_auth_token”, use_auth_token)→ 129 pipeline = Klass(**params)131 # freeze  parameters132 if “freeze” in config:File ~\Anaconda3\envs\Alex\envs\pyannote\lib\site-packages\pyannote\audio\pipelines\speaker_diarization.py:165, in SpeakerDiarization.init(self, segmentation, segmentation_duration, segmentation_step, embedding, embedding_exclude_overlap, clustering, embedding_batch_size, segmentation_batch_size, der_variant, use_auth_token)162     metric = “not_applicable”164 else:→ 165     self._embedding = PretrainedSpeakerEmbedding(166         self.embedding, use_auth_token=use_auth_token167     )168     self._audio = Audio(sample_rate=self._embedding.sample_rate, mono=True)169     metric = self._embedding.metricFile ~\Anaconda3\envs\Alex\envs\pyannote\lib\site-packages\pyannote\audio\pipelines\speaker_verification.py:488, in PretrainedSpeakerEmbedding(embedding, device, use_auth_token)456 “”“Pretrained speaker embedding457458 Parameters(…)484 >>> embeddings = get_embedding(waveforms, masks=masks)485 “””487 if isinstance(embedding, str) and “speechbrain” in embedding:→ 488     return SpeechBrainPretrainedSpeakerEmbedding(489         embedding, device=device, use_auth_token=use_auth_token490     )492 elif isinstance(embedding, str) and “nvidia” in embedding:493     return NeMoPretrainedSpeakerEmbedding(embedding, device=device)File ~\Anaconda3\envs\Alex\envs\pyannote\lib\site-packages\pyannote\audio\pipelines\speaker_verification.py:249, in SpeechBrainPretrainedSpeakerEmbedding.init(self, embedding, device, use_auth_token)246 self.device = device or torch.device(“cpu”)247 self.use_auth_token = use_auth_token→ 249 self.classifier_ = SpeechBrain_EncoderClassifier.from_hparams(250     source=self.embedding,251     savedir=f"{CACHE_DIR}/speechbrain",252     run_opts={“device”: self.device},253     use_auth_token=self.use_auth_token,254 )File ~\Anaconda3\envs\Alex\envs\pyannote\lib\site-packages\speechbrain\pretrained\interfaces.py:342, in Pretrained.from_hparams(cls, source, hparams_file, pymodule_file, overrides, savedir, use_auth_token, revision, **kwargs)340     clsname = cls.name341     savedir = f"./pretrained_models/{clsname}-{hashlib.md5(source.encode(‘UTF-8’, errors=‘replace’)).hexdigest()}"→ 342 hparams_local_path = fetch(343     hparams_file, source, savedir, use_auth_token, revision344 )345 try:346     pymodule_local_path = fetch(347         pymodule_file, source, savedir, use_auth_token, revision348     )File ~\Anaconda3\envs\Alex\envs\pyannote\lib\site-packages\speechbrain\pretrained\fetching.py:135, in fetch(filename, source, savedir, overwrite, save_filename, use_auth_token, revision)133     sourcepath = pathlib.Path(fetched_file).absolute()134     _missing_ok_unlink(destination)→ 135     destination.symlink_to(sourcepath)136 return destinationFile ~\Anaconda3\envs\Alex\envs\pyannote\lib\pathlib.py:1384, in Path.symlink_to(self, target, target_is_directory)1382 if self._closed:1383     self._raise_closed()→ 1384 self._accessor.symlink(target, self, target_is_directory)OSError: [WinError 1314] A required privilege is not held by the client: ‘C:\Users\Alex\.cache\huggingface\hub\models–speechbrain–spkrec-ecapa-voxceleb\snapshots\5c0be3875fda05e81f3c004ed8c7c06be308de1e\hyperparams.yaml’ → ‘C:\Users\Alex\.cache\torch\pyannote\speechbrain\hyperparams.yaml’I thought I needed to accept the Terms and condition on huggingface for thespkrec-ecapa-voxcelebmodel but I couldn’t find something to accept.I scroll the web before posting this message but found nothing.I’m running on windows 10, jupyter notebook with anaconda and python 3.8.Here are the package installedpackage221×577 49.1 KBCan you help me to solve the error ?Thanks a lot !Alex
2023-02-27T13:23:08Z
I found the answer !Jupyter notebook need to be run with admin privilege. Solution ishere
2023-04-07T18:53:11Z
If you trying to run in anaconda prompt or cmd ,launch  as run as administrator.
2023-09-05T09:01:31Z
Hey, I am running into the same issue and unfortunately cannot run it with admin privilege. Do you know any other solution to this issue?
2024-03-29T08:43:28Z
So do you really need admin rights to run this library? Why is this necessary, what if we cannot use admin privileges?
2024-06-22T04:31:09Z
Agree, why will it require Admin Privilege to run this? Doesn’t quite make sense.