Instructions to use optimum-internal-testing/tiny-random-whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use optimum-internal-testing/tiny-random-whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="optimum-internal-testing/tiny-random-whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("optimum-internal-testing/tiny-random-whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("optimum-internal-testing/tiny-random-whisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba6d7230bddfea553ff3df752682385bcbc5e6543cecd122cae16ffef955ec43
- Size of remote file:
- 872 kB
- SHA256:
- f2befb0a67d1d7ce3a6ac707fa894eef12e1b23ce22a0c8fe36cc75ef4c09576
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