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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c19ded90df3033d5d2b715d16dc7c834e77583f72b2cf9f66657cc867a0b3ac4
- Size of remote file:
- 120 kB
- SHA256:
- 27c6dcaeb7cc16d30b3d26b8550a58286ea090745a5f9ee5cc89b667489450cc
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