Automatic Speech Recognition
NeMo
Core ML
PyTorch
speech
audio
Transducer
TDT
FastConformer
Conformer
NeMo
hf-asr-leaderboard
Instructions to use FluidInference/parakeet-tdt-0.6b-v3-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use FluidInference/parakeet-tdt-0.6b-v3-coreml with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("FluidInference/parakeet-tdt-0.6b-v3-coreml") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
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On‑device multilingual ASR model converted to Core ML for Apple platforms. This model powers FluidAudio’s batch ASR and is the same model used in our backend. It supports 25 European languages and is optimized for low‑latency, private, offline transcription.
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## Highlights
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- **Core ML**: Runs fully on‑device (ANE/CPU) on Apple Silicon.
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On‑device multilingual ASR model converted to Core ML for Apple platforms. This model powers FluidAudio’s batch ASR and is the same model used in our backend. It supports 25 European languages and is optimized for low‑latency, private, offline transcription.
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For conversion script and benchmarks:
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https://github.com/FluidInference/mobius/tree/main/models/tts/parakeet-tdt-v3-0.6b/coreml
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## Highlights
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- **Core ML**: Runs fully on‑device (ANE/CPU) on Apple Silicon.
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