Instructions to use onnx-internal-testing/tiny-random-WhisperForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use onnx-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="onnx-internal-testing/tiny-random-WhisperForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("onnx-internal-testing/tiny-random-WhisperForConditionalGeneration") model = AutoModelForSpeechSeq2Seq.from_pretrained("onnx-internal-testing/tiny-random-WhisperForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cea54a638a3f4c772a8635e9b8b0c2d6a8c93c0e328f7158e95dc91fe42171ed
- Size of remote file:
- 1.72 MB
- SHA256:
- 0b3f5eb66199edae4ca571088cb87538b5d767683f839d30594b0dd96fab3645
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