Instructions to use Dmitriy/wav_2_vec_be_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dmitriy/wav_2_vec_be_1 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_1")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Dmitriy/wav_2_vec_be_1") model = AutoModelForCTC.from_pretrained("Dmitriy/wav_2_vec_be_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f13b0ecfba60ca2e3c48bb75b2f2875f008efbd2f8384a4143f07220aa3e4688
- Size of remote file:
- 4.03 kB
- SHA256:
- 345e3c54a151cbce320eb96c118001097364795b61c34b677a2dbef2b699b627
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