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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8ae37002e8d7d0fd83d041408108682730128111b4c223c8b609f1fc89c2317
- Size of remote file:
- 1.26 GB
- SHA256:
- 455418f744560b3cf4356a8df6b0f13e984c0d73c886d371a7d1d61149befed7
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