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
- Xet hash:
- acde7b31874de45fca20d82e451a79beff4b498525a131a2631b16622a2246b6
- Size of remote file:
- 441 MB
- SHA256:
- c5994e0697bd6a47f4ec6b22a310a24c46bca19ec48a54c7f794e9dfa4d11733
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