Instructions to use hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42120c5a483856ce58ba01d802dbfb0274cb0aab18e14fac32f5d1d869a8a9cb
- Size of remote file:
- 136 kB
- SHA256:
- 03e6a49e75cb91d78409821a3ccf305c137b1123a30d18e38485e7e2a598d9a2
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