Instructions to use zacdan4801/wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f4 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-f4 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-f4")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("zacdan4801/wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f4") model = AutoModelForCTC.from_pretrained("zacdan4801/wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc29e4172b4c8c79571eb2dd2ccfe7f00b5d73b6047999e3a57866befe35d1fb
- Size of remote file:
- 1.26 GB
- SHA256:
- c429f864bb022a9025bc849e3e90a72e18b81cfbdfc303d2b92278199e4d2962
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