Comments (2)
I don't know the details, but my guess is that CoreML creates some cache of the model. This might be the reason that the first time it runs on a device it is slow
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Thanks @ggerganov for the reply, yes you are right coreml is making a cache when loading up, however i am deleting the cache on app closure, which should clear it. The container of the app looks normal with all caches deleted, but that value in the "settings -> general -> app storage" still shows many mb (or gbs if used a lot). So i think this must be a bug in the OS file system. If you have time can you quickly load up your app, and then check the size in the iphone settings?
I will ask Apple directly about it and maybe file a bug.
Amazing work btw, everytime i use this in my app it i am amazed at what you have achieved on an iphone!
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Related Issues (20)
- Add log callback for opencl
- WASM examples could not fetch whisper models due to CORS
- apple M1 error
- Dell Inspiron 5593 Intel® Core™ i7-1065G7 CPU @ 1.30GHz × 8
- Cuda doesn't use nvidia GPU
- Nonsense Output At times in spite of silence
- CUBLAS CMAKE issue
- WHISPER_CUDA compile error HOT 1
- [Question] Does Whisper.cpp support Flash Attention V2?
- Loading Whisperkit model via dropdown (top right) does not give warning about initial model activation HOT 1
- Error when initializing context from Java
- Transcription issue with audio files longer than 10 minutes when CUDA is enabled - Linux Ubuntu 20.04
- Cannot compile for HIPBLAS (whisper_mel_calc_create_cuda is undefined) HOT 2
- Segmentation fault with CUDA on commit (#2206) HOT 9
- take more time if using quantized model on Apple Metal HOT 2
- App crashes after live transcribing for awhile
- error with strean HOT 1
- No rule to make target 'stream'. Stop. HOT 1
- Cannot compile for HIPBLAS ( undefined reference due to --no-allow-shlib-undefined: void ggml_cuda_flash_attn_ext_wmma_f16_case )
- running example use too long time in linux
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