With auto-installed dependecies:
>>> recognition_result = model.transcribe_longform("long_example.wav")
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.0.2 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.
If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.
After installing numpy 1.26.4 it works:
>>> recognition_result = model.transcribe_longform("long_example.wav")
INFO:pytorch_lightning.utilities.migration.utils:Lightning automatically upgraded your loaded checkpoint from v1.1.3 to v2.4.0. To apply the upgrade to your files permanently, run `python -m pytorch_lightning.utilities.upgrade_checkpoint ../../.cache/torch/pyannote/models--pyannote--segmentation/snapshots/059e96f964841d40f1a5e755bb7223f76666bba4/pytorch_model.bin`
Model was trained with pyannote.audio 0.0.1, yours is 3.3.2. Bad things might happen unless you revert pyannote.audio to 0.x.
Model was trained with torch 1.7.1, yours is 2.5.1+cu124. Bad things might happen unless you revert torch to 1.x.
>>>
>>> for utterance in recognition_result:
... transcription = utterance["transcription"]
... start, end = utterance["boundaries"]
... print(f"[{gigaam.format_time(start)} - {gigaam.format_time(end)}]: {transcription}")
...
[00:00:00 - 00:16:83]: вечерня отошла давно но в кельях тихо и темно уже и сам игумен строгий свои молитвы прекратил и кости ветхие склонил перекрестясь на одр убогий кругом и сон и тишина но церкви дверь отворена
...........
With auto-installed dependecies:
After installing numpy 1.26.4 it works: