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:
- f9c8d3f0a9cbf00035d419bd15233c8c2d574119ce45109fca575e445fa4087e
- Size of remote file:
- 421 kB
- SHA256:
- 7ec2b768c430943c62e5a4acf2351339ee58a2c718139125bceed267480675da
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