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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 529dcdc9f0218280d5d40a5f87fcb278a2369a2617a38d15dc77b47a5082abe8
- Size of remote file:
- 12.9 MB
- SHA256:
- 04fa29be61a2f54a68c0aee7c55a5e8f38479b460c9fad4da4b9ccd1e1232b2e
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