Comments (1)
You can use any size wav2vec2 model, even Hubert works, and others. The bigger + more finetuning data the better.
But since they havent been tested, check examples to see if they seem reasonable.
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Related Issues (20)
- Execute function diarize_model() threw an exception
- Streaming with whisperx HOT 1
- Crashed by ZeroDivisionError when set "--print_progress True"
- the text was cut before reaching the end time.
- How to use local wav2vec alignment model?
- whisperx error after upgrade HOT 2
- what does the batch size mean HOT 4
- DiarizationPipeline without HF token?
- audio split into 30-sec chunks. What does it mean? HOT 1
- Model evaluation and confidence metrics
- "missing 3 required positional arguments" HOT 5
- How to load a local model by default instead of going to huggingface to find a model first?
- Pyannote model download failing HOT 1
- Pyannote 3.0
- Faster options when running on Mac mini M2 with Ventura 13.5.2 OS?
- When calling ffmpeg, filenames with spaces are truncated
- Error When Running Diarization: KeyError and ValueError Related to DataFrame
- Huggingface Authentication Issues probably related to pyannote HOT 12
- pyannote/speaker-diarization-3.0 runs slower than pyannote/[email protected] HOT 8
- importing whisperx - no module named 'lightning_fabric.utilities'
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