Instructions to use hf-internal-testing/tiny-random-LongformerForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LongformerForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-LongformerForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LongformerForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-LongformerForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6c58cb2b11ec6ace7eb0710c1f0b4c7c127ae531bec4324edad7f992ee5fe58
- Size of remote file:
- 446 kB
- SHA256:
- a11e8724baba284351142e0799288fb4a36e21965f11a7d736dd28a70de24f99
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