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:
- d7643ed06a9beb435e670b9347b3ffd64f6c9f5efb9ace3657d4b05625bd5e9f
- Size of remote file:
- 1.26 GB
- SHA256:
- 3a8b3df0fc8735779c1eb12052c5a623a835fcb173cb04674ffe8d82b38251a4
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