Instructions to use hf-internal-testing/tiny-random-led with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-led with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-led")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-led") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-led") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 338ef046d0879940a6ec902066f2b99743150adaba50f493026b2ba53d93d4c2
- Size of remote file:
- 14.3 MB
- SHA256:
- f0bad309f7ee2974f74839e8414448c5d859900f63cc86f79c8ea6318d248ca9
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