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:
- 8cb8a1cbf73af22bf0fa84b52e5bb3fbfe71602568ce88ca9682921ccce78695
- Size of remote file:
- 3.32 MB
- SHA256:
- 51bd135173e214ece297b311de43bb09692c0589b77ae4df7d9e237eb6dadd3f
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