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:
- 34380471c00cdfd22a0fd83531e8b4c17294cede72fd417e3d865c295561128a
- Size of remote file:
- 141 kB
- SHA256:
- c04bda694dd2df09fc5b3d3df1875d4a3ee5b81cd47c0561e4b92079b7c36266
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