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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8aa89ea76d6e634da156d3f3c1e755220a4cbf186643a4ce36fce779abbedeb
- Size of remote file:
- 12.9 MB
- SHA256:
- ed8f7cac52c6393b49b2bbb61dcb85b270d7202155026836c549ddf5237b99f9
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