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:
- 9afb13192df755b7c0fcf008c63800c6856a985b2756c29717038f54bdc27ff1
- Size of remote file:
- 201 kB
- SHA256:
- a907dc9fbb5f53ef3a9fc013c564a4e863830cf9b275a19aa87986a6918ab784
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