Instructions to use hf-internal-testing/tiny-random-WhisperForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-WhisperForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/tiny-random-WhisperForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-WhisperForConditionalGeneration") model = AutoModelForSpeechSeq2Seq.from_pretrained("hf-internal-testing/tiny-random-WhisperForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f08f2b2100bb1f633ac323950414f02df542823eeff0c258e1d2b92c84108c33
- Size of remote file:
- 3.29 MB
- SHA256:
- 089fb9bb126b062d2a3b4603ee1ad15f14e0ddda58ccfb3b2f186f4ac3b3b6b1
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