Instructions to use hf-internal-testing/tiny-random-WavLMForAudioFrameClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-WavLMForAudioFrameClassification with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForAudioFrameClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-WavLMForAudioFrameClassification") model = AutoModelForAudioFrameClassification.from_pretrained("hf-internal-testing/tiny-random-WavLMForAudioFrameClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23165a899276c40d7b1e10abdecfc99b2cadc9780a332d5d775527fcde4d70b6
- Size of remote file:
- 141 kB
- SHA256:
- 6f0283decad961ecc9c49818f6bcc1aee868e1bc7ebbf7866c0718e2ef8510bb
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