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:
- bde22a1929d4cd12e34f81ccc6cc04334d629bd0788e68329bbb386269fbcbfe
- Size of remote file:
- 141 kB
- SHA256:
- 0d0c8193017f039b0f737cb67b53ffdce0cdde65af1b8fb4623e837bdecb012c
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