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 /Jun23_05-22-39_96dfb9f0fe5a /events.out.tfevents.1687497778.96dfb9f0fe5a.50825.3
- Xet hash:
- b6287bba8eebba81d153b7d26e4103b81073f3c09e9f546c9f4ec61100148ade
- Size of remote file:
- 354 Bytes
- SHA256:
- 344f738d2b751e9598af11268099f47094b8f486fd9d51c3a012b1acf788955c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.