Instructions to use binwang/bert-base-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binwang/bert-base-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="binwang/bert-base-nli")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("binwang/bert-base-nli") model = AutoModelForMaskedLM.from_pretrained("binwang/bert-base-nli") - Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:09f0236af05b8e14cedb931ec3f51f831e376187e1d4d3deff878c629107a21a
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size 437973984
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