Instructions to use GENG/wav2vec2.0_lv60_timi_pr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GENG/wav2vec2.0_lv60_timi_pr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GENG/wav2vec2.0_lv60_timi_pr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GENG/wav2vec2.0_lv60_timi_pr") model = AutoModelForCTC.from_pretrained("GENG/wav2vec2.0_lv60_timi_pr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2dbdd3cd87542c13ab3d7fcfa707089ae3461ebf06f6371d73d724eafccfaac
- Size of remote file:
- 2.29 kB
- SHA256:
- 2baeae1b950fdc46c9651622f18c94afdb100882436f0232f95bdc47d57ec426
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