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:
- c2203661c6459616f5935c5a600210d2cc1eda3e3b7db8059179a0fc5bca7a88
- Size of remote file:
- 1.23 MB
- SHA256:
- b3e8da80ec813131bac8cd45212c6b48b744efd38563cd64efe5015f058b819e
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