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:
- 2b4183cf4ac297882beb2f9a87c05a023624cd716b79054cb908221586063722
- Size of remote file:
- 1.25 MB
- SHA256:
- 018e3f4e99d3f4b6d252de0b6940d7e546cc64ca5a7a97ee84f486aa73a62cb8
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