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 tokenizer_config.json from oruk/orukeet: direct link, hf CLI and curl.
- Browser
- Download file 258 Bytes
-
https://huggingface.co/oruk/orukeet/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://oruk/orukeet/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/oruk/orukeet/resolve/main/tokenizer_config.json
258 Bytes
| { | |
| "backend": "tokenizers", | |
| "clean_up_tokenization_spaces": false, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "processor_class": "ParakeetProcessor", | |
| "tokenizer_class": "ParakeetTokenizer", | |
| "unk_token": "<unk>" | |
| } | |