Instructions to use binwang/bert-large-nli-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binwang/bert-large-nli-stsb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="binwang/bert-large-nli-stsb")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("binwang/bert-large-nli-stsb") model = AutoModelForMaskedLM.from_pretrained("binwang/bert-large-nli-stsb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f922cb2dba649864fad2bb0d8789a3d700c753d22cc52bc5ee8ea9c5b4379fae
- Size of remote file:
- 1.34 GB
- SHA256:
- 8ba7f84c87eeab468ec658eb772b3f1a21d10e1b5e017c7b00561c7698efdc5b
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