Instructions to use theodotus/stt_ua_fastconformer_hybrid_large_pc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use theodotus/stt_ua_fastconformer_hybrid_large_pc with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("theodotus/stt_ua_fastconformer_hybrid_large_pc") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
| language: | |
| - uk | |
| library_name: nemo | |
| datasets: | |
| - mozilla-foundation/common_voice_10_0 | |
| - Yehor/ukrainian-tts-mykyta | |
| - Yehor/ukrainian-tts-lada | |
| - Yehor/ukrainian-tts-tetiana | |
| tags: | |
| - automatic-speech-recognition | |
| model-index: | |
| - name: stt_ua_fastconformer_hybrid_large_pc | |
| results: | |
| - task: | |
| name: Automatic Speech Recognition | |
| type: automatic-speech-recognition | |
| dataset: | |
| name: Mozilla Common Voice 10.0 | |
| type: mozilla-foundation/common_voice_10_0 | |
| config: clean | |
| split: test | |
| args: | |
| language: uk | |
| metrics: | |
| - name: Test WER | |
| type: wer | |
| value: 7.10 | |
| license: mit | |
| # FastConformer Hybrid Transducer-CTC Large P&C (uk-UA) | |
| <style> | |
| img { | |
| display: inline; | |
| } | |
| </style> | |
| | [](#model-architecture) | |
| | [](#model-architecture) | |
| | [](#datasets) | | |
| ## Attribution | |
| As initial checkpoint used [stt_ua_fastconformer_hybrid_large_pc](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_ua_fastconformer_hybrid_large_pc) by [NVIDIA](https://github.com/NVIDIA) licensed under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) |