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:
- ea4343072523d829d4e61d6311b23c15c0b93f7c33a563ebd488db5da7a74814
- Size of remote file:
- 201 kB
- SHA256:
- d521e1c6a81eb39b58782923f79a735eb8ad3c77b1ff8595bfc2f5e3e539d65a
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