Instructions to use onnx-internal-testing/tiny-random-WhisperForConditionalGeneration-ONNX_external 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-ONNX_external 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-ONNX_external")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("onnx-internal-testing/tiny-random-WhisperForConditionalGeneration-ONNX_external") model = AutoModelForSpeechSeq2Seq.from_pretrained("onnx-internal-testing/tiny-random-WhisperForConditionalGeneration-ONNX_external") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7923646ad38a0773b1266e248d911b386fb7673a0bfcd136e45184a5acb7072e
- Size of remote file:
- 3.5 MB
- SHA256:
- 6f4cb4bbdc27b0ba3ea601d08b5f70b7dc56e2ee6f432b65090d2c3e1018d9e9
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