Instructions to use Isma/some_cool_project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isma/some_cool_project with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Isma/some_cool_project")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Isma/some_cool_project") model = AutoModelForCTC.from_pretrained("Isma/some_cool_project") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2124ff63afe77e83ff07ef5df50c134a98e7a5a151ab05a4fe0f2332179f1647
- Size of remote file:
- 3.71 kB
- SHA256:
- ec35edc30eb1eef1602eddeab588fd930af1454b6e48456a2b8bb77f08342661
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