Automatic Speech Recognition
NeMo
Core ML
PyTorch
speech
audio
Transducer
TDT
FastConformer
Conformer
NeMo
hf-asr-leaderboard
Instructions to use codeclawd/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 codeclawd/parakeet-tdt-0.6b-v3-coreml with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("codeclawd/parakeet-tdt-0.6b-v3-coreml") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Download EncoderInt4.mlmodelc/coremldata.bin from codeclawd/parakeet-tdt-0.6b-v3-coreml: direct link, hf CLI and curl.
- Browser
- Download file 512 Bytes
-
https://huggingface.co/codeclawd/parakeet-tdt-0.6b-v3-coreml/resolve/main/EncoderInt4.mlmodelc/coremldata.bin
- Command line
-
hf download hf://codeclawd/parakeet-tdt-0.6b-v3-coreml/EncoderInt4.mlmodelc/coremldata.bin
-
curl -L -o coremldata.bin https://huggingface.co/codeclawd/parakeet-tdt-0.6b-v3-coreml/resolve/main/EncoderInt4.mlmodelc/coremldata.bin
512 Bytes
- Xet hash:
- 2aca776ccbb04657b2bd5b78d561d694e196f387807f80c163e06bd2423c4a73
- Size of remote file:
- 512 Bytes
- SHA256:
- 3e6539cd5d5f1c3bd5a01921cd94af85eab609d49d47e1436a16faac958754d6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.