Instructions to use Devion333/wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devion333/wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Devion333/wav2vec2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Devion333/wav2vec2") model = AutoModelForCTC.from_pretrained("Devion333/wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27ba262857efcffacf684a55428e47b79cab527807c84167921e8fb0e605a024
- Size of remote file:
- 4.02 kB
- SHA256:
- 2a804adcf32db97a8cf360ecba11b680bcce1bdf82cbb6047fa3d288545fa1ee
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