Instructions to use hf-internal-testing/tiny-random-WhisperModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-WhisperModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-WhisperModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-WhisperModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-WhisperModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ebfe81589255cda87130ebe4a4cd4d9868c94e321820d276bd59866b5ea38f21
- Size of remote file:
- 3.28 MB
- SHA256:
- 2bf664dd169bae7ef4fa7c31d0ddd6e11b8636410dd5727736dcdd92d475a47a
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