Automatic Speech Recognition
NeMo
ONNX
Safetensors
GGUF
parakeet_tdt
parakeet
tdt
sherpa-onnx
multilingual
speech-recognition
gabor
fastconformer
Instructions to use oruk/orukeet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use oruk/orukeet with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("oruk/orukeet") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from oruk/orukeet: direct link, hf CLI and curl.
- Browser
- Download file 417 Bytes
-
https://huggingface.co/oruk/orukeet/resolve/refs%2Fpr%2F2/processor_config.json
- Command line
-
hf download hf://oruk/orukeet@refs/pr/2/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/oruk/orukeet/resolve/refs%2Fpr%2F2/processor_config.json
417 Bytes
| { | |
| "blank_token": "<blank>", | |
| "decoder_type": "tdt", | |
| "feature_extractor": { | |
| "feature_extractor_type": "ParakeetFeatureExtractor", | |
| "feature_size": 128, | |
| "hop_length": 160, | |
| "n_fft": 512, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "preemphasis": 0.97, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000, | |
| "win_length": 400 | |
| }, | |
| "processor_class": "ParakeetProcessor" | |
| } | |