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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85a908ceabecca971ef627f531223ba201e8965156e5c056517c80878588f02b
- Size of remote file:
- 201 kB
- SHA256:
- 89e50a2aea2c0868774fad6b8310f45fcf06df70cc9b355da53c9b4ffa3a3ee1
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