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:
- f2e426d5e83e4121f215f369f3da11872392348834efc69beb0319d413a018dc
- Size of remote file:
- 201 kB
- SHA256:
- 0318410c523f74c8a71307e682479f6304acf6d472b9d43ee5526a0c6d37ac42
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