Instructions to use jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-1") model = AutoModelForMaskedLM.from_pretrained("jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50a3009ed98b14afdaf32fa5331e36dc7e7eabd167282e9f64bbb87a9536da37
- Size of remote file:
- 4.03 kB
- SHA256:
- a6fd51b4898506e9ac5aa2a7b658f5df4ac0190967488ae8226ba74b81354fcf
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