Automatic Speech Recognition
NeMo
Safetensors
Transformers
PyTorch
English
parakeet_ctc
speech
audio
FastConformer
Conformer
NeMo
hf-asr-leaderboard
ctc
Eval Results (legacy)
Eval Results
Instructions to use nvidia/parakeet-ctc-0.6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/parakeet-ctc-0.6b with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("nvidia/parakeet-ctc-0.6b") transcriptions = asr_model.transcribe(["file.wav"]) - Transformers
How to use nvidia/parakeet-ctc-0.6b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nvidia/parakeet-ctc-0.6b")# Load model directly from transformers import AutoModelForCTC model = AutoModelForCTC.from_pretrained("nvidia/parakeet-ctc-0.6b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 933d80c10ce9635b5802b12cce50b579f1e3adad69a6292ad349e06b6644e560
- Size of remote file:
- 2.44 GB
- SHA256:
- bc01f3f8f0098b72b6f461d36b01f45a4bc00a2973ab840bd31edab96e605fc9
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