Instructions to use u107/nemo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use u107/nemo with NeMo:
# tag did not correspond to a valid NeMo domain.
- Notebooks
- Google Colab
- Kaggle
Vadim commited on
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README.md
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- _last checkpoint:_ ```jasper10x5/2023-02-22_06-46-21/Jasper10x5--val_loss=1.7606-epoch=4-last.ckpt```
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- _Dataset train:_ **1738252** files totalling **1645.74** hours
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- _Dataset validation:_ **11373** files totalling **12.63** hours
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- _last checkpoint:_ ```jasper10x5/2023-02-22_06-46-21/Jasper10x5--val_loss=1.7606-epoch=4-last.ckpt```
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- _Dataset train:_ **1738252** files totalling **1645.74** hours
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- _Dataset validation:_ **11373** files totalling **12.63** hours
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Використання:
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```python
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from huggingface_hub import hf_hub_download
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from nemo.collections.asr.models import ASRModel
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from omegaconf import OmegaConf
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# filename_model = 'quartznet15x5/2023-02-23_11-43-23/stt_uk_ru_quartznet15x5.nemo'
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# filename_model = 'quartznet15x5/2023-04-04_02-57-02/stt_uk_quartznet15x5.nemo'
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# filename_model = 'jasper10x5/2023-02-22_06-46-21/stt_uk_ru_jasper10x5.nemo'
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filename_model = 'jasper10x5/2023-04-07_05-01-29/stt_uk_jasper10x5.nemo'
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model_path = hf_hub_download(
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repo_id="u107/nemo",
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filename=filename_model,
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repo_type="model",
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cache_dir='/content',
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use_auth_token='hf_...')
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nemo_model = ASRModel.restore_from(
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restore_path=model_path,
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# map_location='CPU',
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# return_config=True,
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) # type: ASRModel
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# зберегти файл налаштувань
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OmegaConf.save(nemo_model.cfg, 'model_config.yaml')
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# відобразити версію nemo на якій було навчання
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print(nemo_model.cfg.nemo_version)
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# відобразити алфавіт
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print(nemo_model.cfg.labels)
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```
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