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:
- d04898bb6a2f3e3d9fb1c13772e0754b9aaafaa8feb5e637b4041109714db5f9
- Size of remote file:
- 4.03 kB
- SHA256:
- 4871d1a2f96539e1d6f3a5defb5322a497630e0bdeba8c1c0274cd866dbf96e3
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