Comments (3)
The issue stems from faster-whisper having not specify a version in requirements.txt:
ctranslate2>=4.0,<5
Leading to the installation of untested versions of CTranslate2:
A few days ago a version 4.2.1 of ctranslate2 came out and installing it creates this problem.
pip installing the package ctranslate2==4.2.0 before installing the whisperx package can solve this problem
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The installed version is cuda11.8
File/usr/local/cuda/lib64/libcublas.so.11 exists
But why would you look for libcublas.so.12?
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I had the same problem. By installing Pytorch version Cuda 12.1 and installing whisperX by Pip, this installed the libcublass and cudnn dependencies automatically.
pip3 install torch torchvision torchaudio
pip install whisperx
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Related Issues (20)
- transcribe audio with "guidance" text as reference HOT 1
- AttributeError: 'Wav2Vec2Processor' object has no attribute 'sampling_rate'
- Diarization Pipeline config on diarize.py HOT 6
- May I ask how C # can use this project
- Audio captions (background sounds, e.g. [applause], [dog barking])
- Keeping the same speaker in different files
- Question about current BSD-4-Clause License HOT 2
- Is there any way to disable VDA?
- ValueError: Requested float16 compute type, but the target device or backend do not support efficient float16 computation HOT 3
- detect_language() doesn't work on a GPU? HOT 2
- Transcription/translation language change -- '50358' / '50359' is not a valid task (accepted tasks: transcribe, translate)
- Wrong cuda device (device_id > 0) on VAD in whisperx.load_model() method
- A tip: color coding the outputs (e.g. srt) from the JSON files HOT 1
- Word Level Transcripts Error HOT 8
- Transcription fails with diarization enabled
- Some transcriptions missing properties HOT 1
- RuntimeError: parallel_for failed: cudaErrorNoKernelImageForDevice: no kernel image is available for execution on the device HOT 5
- Getting no audio found error HOT 1
- whisperx.load_model & default_asr_options Error in Colab HOT 4
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