![]() ![]() I assume it is trading speed for accuracy but I don't understand how/where accuracy is reduced.īeta Was this translation helpful? Give feedback. There is another project: which is much much faster on CPU. On the base.en model it's about twice as fast for me.Īnother option, depending on how much you have to transcribe and any data security concerns is to run whisper within a free Google Colab GPU instance, which ran at about 8x realtime for me on small.en model. Using programs for video conversion, backup, 3D rendering, etc. Here are the top reasons of why Mac computer is running slow: High CPU usage of apps. So if the medium model is 0.05x realtime on your Ryzen 3600 that sounds about right. The first step to diagnosing a system slowdown is to consider the most common reasons that may cause this. ![]() On my Ryzen 4500U on the small.en model transcription is about 0.10x realtime. The first step to diagnosing a system slowdown is to consider the most common reasons that may cause this. ![]() On your CPU the base model may be close to 1x. I've found both base and small models to be very accurate (for English), with most differences between models only being punctuation (tiny model does tend to have more errors though still not that many). Something like an NVIDIA GTX 1660 would be ~10x the speed of a 6/8 core CPU. CPU is very slow, particularly on the larger models. ![]()
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