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 /May22_11-55-33_e991b00007ed /events.out.tfevents.1684756555.e991b00007ed.50811.5
- Xet hash:
- cb2ad7ae917c36e2761c3aea7b1c7c1560d7e612f7e1ee8958024676d5ead6df
- Size of remote file:
- 354 Bytes
- SHA256:
- 6ed10fc54cc2a0bed5714def4aa49bf881edb8bae702ac79278d2db7aaab0c38
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