Instructions to use Dmitriy/wav_2_vec_be with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dmitriy/wav_2_vec_be with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Dmitriy/wav_2_vec_be")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Dmitriy/wav_2_vec_be") model = AutoModelForCTC.from_pretrained("Dmitriy/wav_2_vec_be") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 167cae0b1ad3d92ea418a799ed12ca5cd40a7f9731931f532b0d3c7a58b432b9
- Size of remote file:
- 1.26 GB
- SHA256:
- 6d1c18285230000696c60069dad65de3a7274bac28ec63bf0f4c9fad545c99c1
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