Instructions to use doooori/wav2vec2_pisets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use doooori/wav2vec2_pisets with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="doooori/wav2vec2_pisets")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("doooori/wav2vec2_pisets") model = AutoModelForCTC.from_pretrained("doooori/wav2vec2_pisets") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- effac078b4ea41a1db4e2f1bd37f2b7ef8013ad36032137105203cfb723604af
- Size of remote file:
- 3.39 kB
- SHA256:
- 64f56340b57dd847cb72ced9535f9452d343cc6080bb462f68349010be53353f
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