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:
- 178008ebc853d7ca8d4a949ba77a1b42e9bf1daac6e385e62e283449a7390055
- Size of remote file:
- 141 kB
- SHA256:
- 0fd63df0068021fd0a65411f3b245b5780b30b5b42f8a3d54b6262d25cd81d13
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