Instructions to use tbs17/MathBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tbs17/MathBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tbs17/MathBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tbs17/MathBERT") model = AutoModelForMaskedLM.from_pretrained("tbs17/MathBERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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'token_str': 'cook'}]
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This bias will also affect all fine-tuned versions of this model.--->
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Training data
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The MathBERT model was pretrained on pre-k to HS math curriculum (engageNY, Utah Math, Illustrative Math), college math books from openculture.com as well as graduate level math from arxiv math paper abstracts. There is about 100M tokens got pretrained on.
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#### Training procedure
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'token_str': 'cook'}]
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This bias will also affect all fine-tuned versions of this model.--->
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#### Training data
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The MathBERT model was pretrained on pre-k to HS math curriculum (engageNY, Utah Math, Illustrative Math), college math books from openculture.com as well as graduate level math from arxiv math paper abstracts. There is about 100M tokens got pretrained on.
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#### Training procedure
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