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:
- 01c7690961f33f69c46d650b4e4079bd5975f4e985dff4d70686f1c1bbe8a524
- Size of remote file:
- 1.23 MB
- SHA256:
- f1342020f9f72f80574bcd2632b4526aceb35f082ce59d514e2f6753df7abc80
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