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
bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-1 / runs /May31_03-45-05_4e3381825ef5 /events.out.tfevents.1685505035.4e3381825ef5.2650.5
- Xet hash:
- c84e4fd8d5eaf6fcf449536f157688202c1ea1293af5bbc1a1cda338e44ec1f1
- Size of remote file:
- 354 Bytes
- SHA256:
- bd50b588a764a658059658bdd8a0a19e12573d6a4448dff8edc5730440c4c9ac
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