Instructions to use hf-internal-testing/tiny-random-ClapModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ClapModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-ClapModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-ClapModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ClapModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a0953bfc2ccde013ced9e097b5823d93598a889c9a585fc6e371d7abcdfda32
- Size of remote file:
- 12.8 MB
- SHA256:
- 9ba16aed64a6f56bd976dcad45db9990ef4ea605a8450b231edb9a691300b6f1
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