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, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-WhisperModel") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-WhisperModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec582b6d8b4483c49c6f6d4fec7ace71ec1c512d218fb1d1e865a85d2a2994dc
- Size of remote file:
- 3.3 MB
- SHA256:
- a59d73a5c6565c805fa2cc95122d6e1d5228beb20c42baa92722f40c88c83b85
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