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-1.1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/parakeet-ctc-1.1b with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("nvidia/parakeet-ctc-1.1b") transcriptions = asr_model.transcribe(["file.wav"]) - Transformers
How to use nvidia/parakeet-ctc-1.1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nvidia/parakeet-ctc-1.1b")# Load model directly from transformers import AutoModelForCTC model = AutoModelForCTC.from_pretrained("nvidia/parakeet-ctc-1.1b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 314 Bytes
e576832 a707e81 e576832 c32c0c5 a707e81 e576832 a707e81 e576832 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"feature_extractor_type": "ParakeetFeatureExtractor",
"feature_size": 80,
"hop_length": 160,
"n_fft": 512,
"padding_side": "right",
"padding_value": 0.0,
"preemphasis": 0.97,
"processor_class": "ParakeetProcessor",
"return_attention_mask": true,
"sampling_rate": 16000,
"win_length": 400
}
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