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aufklarer/Whisper-Large-v3-Turbo-CoreML
Whisper-Large-v3-Turbo-CoreML is a automatic speech recognition model from aufklarer. Use it when you need speech turned into text. It is set up for coreml. The card lists the license as mit.
Compiled CoreML bundle for OpenAI Whisper large-v3-turbo, staged for Apple-platform ASR in speech-swift.
Downloads · 30 days
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17% of all-time downloads
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From the Hugging Face model README
Compiled CoreML bundle for OpenAI Whisper large-v3-turbo, staged for Apple-platform ASR in speech-swift.
Part of the soniqo.audio speech toolkit. This is the Apple CoreML bundle used by the native WhisperASR runtime in
speech-swift. Browse Apple bundles in the CoreML Speech Models collection.
| Base model | openai/whisper-large-v3-turbo |
| Bundle source | argmaxinc CoreML bundle |
| Format | Compiled CoreML .mlmodelc |
| Runtime | speech-swift WhisperASR / CoreML |
| Total artifact size | 1562.56 MiB |
| Conversion | Precompiled upstream CoreML bundle, staged for soniqo runtimes |
The bundle splits Whisper into CoreML programs for mel extraction, audio encoding, context prefill, and token decoding. speech-swift loads these programs through its native WhisperASR runtime for Apple Silicon and iOS/macOS deployment.
| File | Size | Description |
|---|---|---|
AudioEncoder.mlmodelc/analytics/coremldata.bin | 0.0 MB | Audio encoder CoreML program |
AudioEncoder.mlmodelc/coremldata.bin | 0.0 MB | Audio encoder CoreML program |
AudioEncoder.mlmodelc/metadata.json | 0.0 MB | Audio encoder CoreML program |
AudioEncoder.mlmodelc/model.mil | 6.84 MB | Audio encoder CoreML program |
AudioEncoder.mlmodelc/model.mlmodel | 0.42 MB | Audio encoder CoreML program |
AudioEncoder.mlmodelc/weights/weight.bin | 1214.96 MB | Audio encoder CoreML program |
MelSpectrogram.mlmodelc/analytics/coremldata.bin | 0.0 MB | Mel spectrogram CoreML program |
MelSpectrogram.mlmodelc/coremldata.bin | 0.0 MB | Mel spectrogram CoreML program |
MelSpectrogram.mlmodelc/metadata.json | 0.0 MB | Mel spectrogram CoreML program |
MelSpectrogram.mlmodelc/model.mil | 0.01 MB | Mel spectrogram CoreML program |
MelSpectrogram.mlmodelc/weights/weight.bin | 0.36 MB | Mel spectrogram CoreML program |
TextDecoder.mlmodelc/analytics/coremldata.bin | 0.0 MB | Token decoder CoreML program |
TextDecoder.mlmodelc/coremldata.bin | 0.0 MB | Token decoder CoreML program |
TextDecoder.mlmodelc/metadata.json | 0.0 MB | Token decoder CoreML program |
TextDecoder.mlmodelc/model.mil | 0.13 MB | Token decoder CoreML program |
TextDecoder.mlmodelc/model.mlmodel | 0.11 MB | Token decoder CoreML program |
TextDecoder.mlmodelc/weights/weight.bin | 328.0 MB | Token decoder CoreML program |
TextDecoderContextPrefill.mlmodelc/analytics/coremldata.bin | 0.0 MB | Token decoder CoreML program |
TextDecoderContextPrefill.mlmodelc/coremldata.bin | 0.0 MB | Token decoder CoreML program |
TextDecoderContextPrefill.mlmodelc/metadata.json | 0.0 MB | Token decoder CoreML program |
TextDecoderContextPrefill.mlmodelc/model.mil | 0.0 MB | Token decoder CoreML program |
TextDecoderContextPrefill.mlmodelc/weights/weight.bin | 11.72 MB | Token decoder CoreML program |
config.json | 0.0 MB | Whisper / generation configuration |
generation_config.json | 0.0 MB | Whisper / generation configuration |
M5 Pro, speech-swift native WhisperASR benchmark, full local FLEURS test split:
| Dataset | WER | CER | Mean RTF | Overall throughput |
|---|---|---|---|---|
fleurs-en_us | 5.55% | 2.72% | 0.065 | 16.7x |
fleurs-fr_fr | 6.28% | 2.70% | 0.075 | 14.0x |
fleurs-ar_eg | 16.60% | 5.63% | 0.082 | 12.8x |
Used by speech-swift through the native WhisperASR runtime:
speech transcribe /path/to/audio.wav \
--engine whisper \
--model aufklarer/Whisper-Large-v3-Turbo-CoreML \
--language en