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:
- 6c2b40060d8a4c4a0daaa409cf1e7f43452f5e82745fb5114492d7874e62302e
- Size of remote file:
- 291 kB
- SHA256:
- 3d9f443957e88a770576bb7f264a8fc6a8c702d707fcd4d430f05152a47cb578
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