Open everypidigit opened 8 months ago
provide more info about your system (hardware / os / python)
also pip install nvidia-cublas-* nvidia-cudnn-*
is unnecessary, that's not how to change cuda version
any updates here i'm getting the same error.
I am getting this error, too
In my case, the issue arose due to the presence of multiple "libiomp5md.dll" files, which caused a conflict.
For example, I found this file in three different folders as following:
C:\ProgramData\anaconda3\envs\p04\Lib\site-packages\ctranslate2\libiomp5md.dll C:\ProgramData\anaconda3\envs\p04\Lib\site-packages\torch\lib\libiomp5md.dll C:\ProgramData\anaconda3\envs\p04\Library\bin\libiomp5md.dll
and I renamed the last one to "libiomp5md_save.dll", and solved the error.
I fixed this error by converting the file .ipynb to a .py file. I don't know why but it works for me. Remember export LD_LIBRARY_PATH
import os
os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
This works for me!
Downgrade ctranslate2 to 4.40
!pip install ctranslate2==4.4.0
Downgrade ctranslate2 to 4.40
!pip install ctranslate2==4.4.0
Thanks! This worked for me!
Downgrade ctranslate2 to 4.40
!pip install ctranslate2==4.4.0
It works, too
My Computer Settings
I've been trying to make faster-whisper run on CUDA the whole day and it just does not work.
The model get initialized on CUDA with no issues, but when I try to actually run the model, it crashes the kernel.
The actual error message:
text: "Kernel Restarting. The kernel for _SHARED/test.ipynb appears to have died. It will restart automatically"
I installed pytorch to a fresh Conda environment using this command from official Pytorch site:
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
Then, I ran:
pip install nvidia-cublas-cu11 nvidia-cudnn-cu11
export LD_LIBRARY_PATH=python3 -c 'import os; import nvidia.cublas.lib; import nvidia.cudnn.lib; print(os.path.dirname(nvidia.cublas.lib.__file__) + ":" + os.path.dirname(nvidia.cudnn.lib.__file__))'
Code I was trying to run when I got the error:
I tried: 1) Installing 12th version cuda with:
pip install nvidia-cublas-cu12 nvidia-cudnn-cu12
2) Downgrading to faster-whisper 0.10.1 3) Downgrading to faster-whisper 0.10.1 and installing 11th version cuda with:pip install nvidia-cublas-cu11 nvidia-cudnn-cu11
Could someone help me with this thing? It runs perfectly on the CPU, but the speed is lacking.