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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af5e2577aab26f4fbdb2ce2d0c1c988b0145d9ad28f33d5b2c6509ffe8aa356d
- Size of remote file:
- 3.33 MB
- SHA256:
- 1925a452e1da67cc341d81b45ed1bd5e2e2e67fd1d0d6af3ecf6b04348be3142
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