Doesn't work in Electron.js's Node

Hi,

I'm trying to use this in Electron but it fails when transcribing with a vague error, I Googled it but didn't find anything
```
aheads_masks_init: dtw_n_top must be between 1 and 4 for this model.whisper_init_state: aheads_masks_init() failed for alignment heads masks
```

I have tried different models and toggling GPU option but no luck so far.

Full log:
```
whisper_init_from_file_with_params_no_state: loading model from '/Users/neo/.smart-whisper/models/ggml-large-v3-turbo-q8_0.bin'
whisper_init_with_params_no_state: use gpu = 0
whisper_init_with_params_no_state: flash attn = 0
whisper_init_with_params_no_state: gpu_device = 0
whisper_init_with_params_no_state: dtw = 16
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 = 4
whisper_model_load: n_mels = 128
whisper_model_load: ftype = 7
whisper_model_load: qntvr = 2
whisper_model_load: type = 5 (large v3)
whisper_model_load: adding 1609 extra tokens
whisper_model_load: n_langs = 100
whisper_model_load: CPU total size = 873.55 MB
whisper_model_load: model size = 873.55 MB

whisper_print_timings: load time = 342.46 ms
whisper_print_timings: total time = 342.48 ms
whisper_init_state: kv self size = 31.46 MB
whisper_init_state: kv cross size = 31.46 MB
whisper_init_state: kv pad size = 7.86 MB
aheads_masks_init: dtw_n_top must be between 1 and 4 for this model.whisper_init_state: aheads_masks_init() failed for alignment heads masks
✨ Done in 10.68s.
```

The issue names no source file, test, or entry point; start by reproducing transcription in Electron with the reported large-v3 model and reviewing the whisper initialization log. Done means transcription works in the Electron Node environment, or the supported model/configuration and failure are clearly documented.

Written by the indexing model from the issue text.