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
Commit ·
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Parent(s): 73c3c14
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:1703573ba71ca6378d0229d511af0da3c0cddcd980ca3a74465b83290c11fa23
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size 438064459
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