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:
- 3dad7ad6c81109decbfc3de7e4e10b25dc4eb2cb2a928b105be6f0a7c4c53f48
- Size of remote file:
- 438 MB
- SHA256:
- 1703573ba71ca6378d0229d511af0da3c0cddcd980ca3a74465b83290c11fa23
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