Instructions to use binwang/bert-base-nli-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binwang/bert-base-nli-stsb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="binwang/bert-base-nli-stsb")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("binwang/bert-base-nli-stsb") model = AutoModelForMaskedLM.from_pretrained("binwang/bert-base-nli-stsb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9a044e5997cfa5e94f1b74ce15b37de721f404ba4c5e4279c89107fb9edc1ad
- Size of remote file:
- 438 MB
- SHA256:
- 11948f21e519851454beee7ec8a5c258071c2986eff47630dc575e291d042bed
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