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 /May16_13-33-41_255a6d5ff38d /events.out.tfevents.1684244028.255a6d5ff38d.29458.5
- Xet hash:
- 46b7dd9e5478f89b8818245c1e00485a2fa1340d0366f81c7e19e37ba8d3f715
- Size of remote file:
- 354 Bytes
- SHA256:
- dc7080219afbec1a14a555fcf1df827be368efb6e3e784f493365227e5a2dae3
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