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
| 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](https://github.com/istupakov/onnx-asr) | |
| and the [ovos-stt-plugin-onnx-asr](https://github.com/OpenVoiceOS/ovos-stt-plugin-onnx-asr) | |
| plugin. Ships both fp32 and int8 weights. | |
| Language: **Esperanto**. Converted from [nvidia/stt_eo_conformer_ctc_large](https://huggingface.co/nvidia/stt_eo_conformer_ctc_large). | |
| ```python | |
| import onnx_asr | |
| model = onnx_asr.load_model("OpenVoiceOS/nvidia-eo-conformer-ctc-large-onnx") | |
| print(model.recognize("audio.wav")) | |
| ``` | |