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:
- c2b86394efc062dcea70701909448b59c274d4346b48630431e41cfd58de5d62
- Size of remote file:
- 77.3 kB
- SHA256:
- e2eea0a5c6b69741883c20438913002ba7266c44ddd152b78dc0fcf8a7f5db73
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