Instructions to use zacdan4801/wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zacdan4801/wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="zacdan4801/wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f3")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("zacdan4801/wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f3") model = AutoModelForCTC.from_pretrained("zacdan4801/wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3b97074028c0dc2dea02a4ae41f9a5408819301ebc0042804c9c5c24ec9c379
- Size of remote file:
- 1.26 GB
- SHA256:
- 170128c5ac8f67384617a6c9be11dbfb2f856ead4b6337da0848ffee84a232e3
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