Instructions to use witiko/mathberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use witiko/mathberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="witiko/mathberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("witiko/mathberta") model = AutoModelForMaskedLM.from_pretrained("witiko/mathberta") - Inference
- Notebooks
- Google Colab
- Kaggle
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@inproceedings{novotny2022combining,
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booktitle = {Proceedings of the Working Notes of {CLEF} 2022},
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title = {Combining Sparse and Dense Information Retrieval},
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subtitle = {Soft Vector Space Model and MathBERTa at ARQMath-3},
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author = {Novotný, Vít and Štefánik, Michal},
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publisher = {{CEUR-WS}},
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year = {2022},
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@inproceedings{novotny2022combining,
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booktitle = {Proceedings of the Working Notes of {CLEF} 2022},
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title = {Combining Sparse and Dense Information Retrieval},
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subtitle = {Soft Vector Space Model and MathBERTa at ARQMath-3 Task 1 (Answer Retrieval)},
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author = {Novotný, Vít and Štefánik, Michal},
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publisher = {{CEUR-WS}},
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year = {2022},
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