Instructions to use hf-internal-testing/tiny-random-longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-longformer")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-longformer") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-longformer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0ac33abb135a9541851ba7727a6365d56b23a94002e6098acdacd00f3f4f30a
- Size of remote file:
- 412 kB
- SHA256:
- b4dddd7df380992d953929ca191d408b92495d7c286f4b1818e5239d29cb6f0e
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