Instructions to use hf-internal-testing/tiny-random-Wav2Vec2ConformerForAudioFrameClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2ConformerForAudioFrameClassification with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForAudioFrameClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ConformerForAudioFrameClassification") model = AutoModelForAudioFrameClassification.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ConformerForAudioFrameClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7eea3c9a7dbb9f0a226cc32a326714f90a3d4828a649751c75576032f211f40
- Size of remote file:
- 166 kB
- SHA256:
- b2dd81b094b13754201ceb80cd7ca3ced868739b89b74da5a2d4585015a8ffad
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