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:
- f119f3e98380f743d8fea0ce47ec505359fe157c7bc924f3bf59715d0088b2c8
- Size of remote file:
- 141 kB
- SHA256:
- 3f99e4738f3558f278f1fb10cddb4c1adb4a2bb6efc777ef5c09118fbddc5a96
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