Instructions to use hf-internal-testing/tiny-random-LongformerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LongformerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-LongformerModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LongformerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-LongformerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48122f69c5040688af7789a3a8563d0c85adeafff09e623f6c38cd294fc563b9
- Size of remote file:
- 415 kB
- SHA256:
- 6a7839e12e85d7500dd35b24102fccce01c2626e9c38e4f4af2e11e2c55bb6f3
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