Instructions to use hf-internal-testing/tiny-random-WavLMModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-WavLMModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-WavLMModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-WavLMModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-WavLMModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46a9ff45436f8053427faa3c7ffeaa4dfc2221b421d18d9a775f7c02648ff4a4
- Size of remote file:
- 140 kB
- SHA256:
- 281b5760ce949a8af9c1692fd09ecf1758a56e9b45f44ee821df06763676dcf0
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