mllife

@wolfshow, nothing is mentioned in the DiT folder, means it is MIT? and we can use it for our custom usage after training? @KananVyas, any update on this?

> os.environ["HF_DATASETS_OFFLINE"] = "1" > os.environ['TRANSFORMERS_CACHE'] = diarization_path > os.environ['TORCH_HOME'] = diarization_path > os.environ['HF_HOME'] = diarization_path > os.environ['PYANNOTE_CACHE'] = diarization_path can you shed some more details on the code changes...

@ExtReMLapin , I download all the files and converted them to actual files from symlinks. But, still ``` diarization_model = Pipeline.from_pretrained( checkpoint_path="./diarization_model/models--pyannote--speaker-diarization/snapshots/2c6a571d14c3794623b098a065ff95fa22da7f25/" ) ``` giving error ``` Traceback (most recent...

@ExtReMLapin , can you take a look my previous comment

@ExtReMLapin model files are now loading from offline cache after I added the env vars. but I still have to use "use_auth_token" in the code. what changes to do in...

@ExtReMLapin , this is the full error ``` Traceback (most recent call last): File "/Users/xXOL/Projects/annotations/check_pyannote_offline.py", line 18, in diarization_model = Pipeline.from_pretrained( File "/Users/xXOL/Projects/annotations/venv/lib/python3.8/site-packages/pyannote/audio/core/pipeline.py", line 88, in from_pretrained config_yml = hf_hub_download(...

The model loaded is None. If I don't add "use_auth_token" @ExtReMLapin , can you share full code snippet of how you are processing a sample.wav file?

thanks, will wait for the update.

@ExtReMLapin , thanks for your detailed response. But i am unable to install the modules required due to conflicts. ``` The conflict is caused by: The user requested pyannote.core==5.0.0 pyannote-algorithms...

recently, sagemaker have updated the default pytorch kernel to py3.10 with cuda 11.8; so now pyannote is not working properly there