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
| { | |
| "encoders": { | |
| "Encoder.mlmodelc": { | |
| "weight_format": "palettized_lut6_mixed_fp16", | |
| "note": "original export; labeled int8 historically, actual compression is 6-bit LUT palettization" | |
| }, | |
| "Encoder_v2.mlmodelc": { | |
| "weight_format": "int8_linear_per_channel", | |
| "source_precision": "fp16", | |
| "fixes": "https://github.com/FluidInference/FluidAudio/issues/760" | |
| }, | |
| "EncoderInt4.mlmodelc": { | |
| "weight_format": "int4" | |
| } | |
| } | |
| } | |