Instructions to use tbs17/MathBERT-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tbs17/MathBERT-custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tbs17/MathBERT-custom")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tbs17/MathBERT-custom") model = AutoModelForMaskedLM.from_pretrained("tbs17/MathBERT-custom") - Notebooks
- Google Colab
- Kaggle
add mathBERT-custom files
Browse files- custom-vocab.txt +0 -0
- pytorch_model.bin +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +3 -0
custom-vocab.txt
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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:c5994e0697bd6a47f4ec6b22a310a24c46bca19ec48a54c7f794e9dfa4d11733
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size 440514422
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tokenizer.json
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tokenizer_config.json
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{
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"do_lower_case": true
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}
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