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
Added small description
Browse files
README.md
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---
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license: mit
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---
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---
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language:
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- uk
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library_name: nemo
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datasets:
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- mozilla-foundation/common_voice_10_0
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- Yehor/ukrainian-tts-mykyta
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- Yehor/ukrainian-tts-lada
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- Yehor/ukrainian-tts-tetiana
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tags:
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- automatic-speech-recognition
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model-index:
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- name: stt_ua_fastconformer_hybrid_large_pc
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Mozilla Common Voice 10.0
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type: mozilla-foundation/common_voice_10_0
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config: clean
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split: test
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args:
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language: uk
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metrics:
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- name: Test WER
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type: wer
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value: 7.07
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license: mit
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---
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# FastConformer Hybrid Transducer-CTC Large P&C (uk-UA)
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<style>
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img {
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display: inline;
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}
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</style>
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| [](#model-architecture)
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| [](#model-architecture)
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| [](#datasets) |
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## Attribution
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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/)
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