Instructions to use OpenVoiceOS/nvidia-eo-conformer-ctc-large-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use OpenVoiceOS/nvidia-eo-conformer-ctc-large-onnx with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("OpenVoiceOS/nvidia-eo-conformer-ctc-large-onnx") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
metadata
license: cc-by-4.0
language:
- eo
library_name: onnx-asr
base_model:
- nvidia/stt_eo_conformer_ctc_large
tags:
- automatic-speech-recognition
- onnx
- nemo
pipeline_tag: automatic-speech-recognition
nvidia-eo-conformer-ctc-large-onnx
ASR model exported to ONNX for onnx-asr and the ovos-stt-plugin-onnx-asr plugin. Ships both fp32 and int8 weights.
Language: Esperanto. Converted from nvidia/stt_eo_conformer_ctc_large.
import onnx_asr
model = onnx_asr.load_model("OpenVoiceOS/nvidia-eo-conformer-ctc-large-onnx")
print(model.recognize("audio.wav"))