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:
- 78a8e4a47765b6472c8dcd769ac86573e9935f3526c3ae0923ea3a11299d7085
- Size of remote file:
- 201 kB
- SHA256:
- 7a2ff6bbe4222ad38988b87ebc124beba56f861ae3ca58862e76837eeaae9b72
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