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New transcription implementation using Whisper #1823
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I have some sad news regarding Whisper-JAX, I managed to run it on Linux. Unfortunately it took a bit more than 4h to transcribe my 29h test data set using Whisper medium model and running on one RTX3090. It also used a ton of GPU memory, about 19GB to load the medium model, while standard Whisper uses about 11GB and Faster-Whisper about 5GB, both for the larger model. Faster-Whisper took about 3h to do the same job using the medium model. So, given the much higher memory usage and a bit slower performance of Whisper-JAX, at least on the hardware we have, Faster-Whisper seems a better option. |
PS: JAX support on Windows is also experimental and CPU only. |
You probably already know, but Whisper runs very smoothly with PyTorch using CUDA 11.6. In fact, the best GUI implementation I've seen is this one: https://grisk.itch.io/whisper-gui. I'm eagerly awaiting Whisper on IPED. |
We plan to integrate Whisper in version 4.2.0, to be released in some months. If you can't wait, there is a starting draft code here: |
I tested this whisper-gui and it's surprisingly fast, but I don't think the source is open source. |
Starting to work on this... |
Wonderful. Any release date forecast? |
Hopefully next month. |
For those interested, a snapshot with this feature will be created here in a few minutes: |
As asked on #1335, we can offer Whisper for users and they can decide if they will pay the performance cost or not. Still not sure which would be better: Faster-Whisper or Whisper-JAX.
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