Instructions to use hf-tiny-model-private/tiny-random-ClapModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ClapModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-ClapModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ClapModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ClapModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a61519818cbf6e90cb56866d011e00be6d9feb6e280e43e6c8baa88a2705fcc
- Size of remote file:
- 12.8 MB
- SHA256:
- c67a45619955df0a9a6e1ab4868984580a37d74becea51727b846069775ea2b8
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