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:
- ada583b62aafd9e5bf5803f5cb4d1ff4ff21342b1aeb9ee5bd4666daf955c49e
- Size of remote file:
- 12.9 MB
- SHA256:
- a752ff121503526709bc66c214027808353bd4f550cc9beb3acacca52d8b7cc0
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