Instructions to use wandererupak/testing-testing-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wandererupak/testing-testing-testing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="wandererupak/testing-testing-testing")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("wandererupak/testing-testing-testing") model = AutoModelForCTC.from_pretrained("wandererupak/testing-testing-testing") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4990dfa9936897ec8907c03712cb09016e619d15f4b8731de7f52ce960c47d1d
- Size of remote file:
- 2.42 GB
- SHA256:
- 04385abee68dd839e3a72fb6c1db49119ade7a79381a62a712f9ffd90083128a
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