Instructions to use othrif/wav2vec_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use othrif/wav2vec_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="othrif/wav2vec_test")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("othrif/wav2vec_test") model = AutoModelForCTC.from_pretrained("othrif/wav2vec_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c222e7f8f969e0655bd58019638971f1ec23e2950fbe1f99316b1a984842707e
- Size of remote file:
- 2.49 GB
- SHA256:
- 0afe7313e3a58ee05f77356220557a12a7999c69667fff22cb67ac4ec07f91cc
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