Instructions to use hf-internal-testing/tiny-random-CanineModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-CanineModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-CanineModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-CanineModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-CanineModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c7096f12bb7ee470d0c9216031be510b8ecf0d87b6988913d567ce5cfcc5316
- Size of remote file:
- 4.46 MB
- SHA256:
- 17b426cce06cff26c3c9b459690f3b6ebd4a25b7d72732d0b9e5fede72067af0
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