coreml: use the correct n_mel

[jxy]

fix coreml for large-v3

$ ./main -m models/ggml-large.bin -f samples/jfk.wav            
whisper_init_from_file_with_params_no_state: loading model from 'models/ggml-large.bin'
whisper_model_load: loading model
whisper_model_load: n_vocab       = 51866
whisper_model_load: n_audio_ctx   = 1500
whisper_model_load: n_audio_state = 1280
whisper_model_load: n_audio_head  = 20
whisper_model_load: n_audio_layer = 32
whisper_model_load: n_text_ctx    = 448
whisper_model_load: n_text_state  = 1280
whisper_model_load: n_text_head   = 20
whisper_model_load: n_text_layer  = 32
whisper_model_load: n_mels        = 128
whisper_model_load: ftype         = 1
whisper_model_load: qntvr         = 0
whisper_model_load: type          = 5 (large v3)
whisper_model_load: adding 1609 extra tokens
whisper_model_load: n_langs       = 100
whisper_model_load: model ctx     = 2951.63 MB
whisper_model_load: model size    = 2951.01 MB
whisper_init_state: kv self size  =   70.00 MB
whisper_init_state: kv cross size =  234.38 MB
whisper_init_state: loading Core ML model from 'models/ggml-large-encoder.mlmodelc'
whisper_init_state: first run on a device may take a while ...
whisper_init_state: Core ML model loaded
whisper_init_state: compute buffer (conv)   =   10.35 MB
whisper_init_state: compute buffer (cross)  =    8.89 MB
whisper_init_state: compute buffer (decode) =   59.40 MB
whisper_init_state: Metal context initialized
whisper_init_state: max tensor size =   126.63 MB

system_info: n_threads = 4 / 8 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | METAL = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | COREML = 1 | OPENVINO = 0 | 

main: processing 'samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 processors, lang = en, task = transcribe, timestamps = 1 ...


[00:00:00.000 --> 00:00:03.000]   And so my fellow Americans,
[00:00:03.000 --> 00:00:08.000]   ask not what your country can do for you,
[00:00:08.000 --> 00:00:11.000]   ask what you can do for your country.


whisper_print_timings:     load time =  1287.51 ms
whisper_print_timings:     fallbacks =   0 p /   0 h
whisper_print_timings:      mel time =     5.79 ms
whisper_print_timings:   sample time =     9.90 ms /    31 runs (    0.32 ms per run)
whisper_print_timings:   encode time =  1238.65 ms /     1 runs ( 1238.65 ms per run)
whisper_print_timings:   decode time =   861.43 ms /    30 runs (   28.71 ms per run)
whisper_print_timings:   prompt time =    45.03 ms /     1 runs (   45.03 ms per run)
whisper_print_timings:    total time =  6412.64 ms