Instructions to use SamuelM0422/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamuelM0422/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SamuelM0422/whisper-tiny-en")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("SamuelM0422/whisper-tiny-en") model = AutoModelForMultimodalLM.from_pretrained("SamuelM0422/whisper-tiny-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d75be4703763abe348f68a977599b2deb202c153f35475c1cc39ee8e6aa2207c
- Size of remote file:
- 151 MB
- SHA256:
- da2e5192a44349708b3d4c1c12b00b40216e6391fbcc8c3518f60372368c0ec0
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