Instructions to use hf-internal-testing/tiny-random-Data2VecAudioModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecAudioModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Data2VecAudioModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecAudioModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Data2VecAudioModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 812aeceea82f3a55eea263948eb90eaca4ff1ddf843b5f095ea5216f0b689e5f
- Size of remote file:
- 267 kB
- SHA256:
- f4dfd2bb389d2928369e178e087f5ca3335f2a10690f600f23b3ee5769a4f99d
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